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How to find a job with ETL skills

How is ETL used?

Zippia reviewed thousands of resumes to understand how etl is used in different jobs. Explore the list of common job responsibilities related to etl below:

  • Developed ETL processes and expanded existing Custom DSS to incorporate additional new customer requirements data source and functionality using OWB.
  • Involved in designing ETL batch production process and developed production support guide documents including process dependency.
  • Translated the high-level design requirements of reliability indicators into Detail design and ETL mapping specifications.
  • Developed and documented ETL standards and guidelines for company-wide usage.
  • Designed extraction, transformation and loading specifications for ETL developers.
  • Designed and implemented Data Warehouse transformations, developed ETL processes.

Are ETL skills in demand?

Yes, etl skills are in demand today. Currently, 10,457 job openings list etl skills as a requirement. The job descriptions that most frequently include etl skills are data warehouse consultant, ssis developer, and database tester.

How hard is it to learn ETL?

Based on the average complexity level of the jobs that use etl the most: data warehouse consultant, ssis developer, and database tester. The complexity level of these jobs is intermediate.

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What jobs can you get with ETL skills?

You can get a job as a data warehouse consultant, ssis developer, and database tester with etl skills. After analyzing resumes and job postings, we identified these as the most common job titles for candidates with etl skills.

Data Warehouse Consultant

  • Data Quality
  • ETL
  • Oracle Sql
  • Data Warehouse
  • Provisioning
  • PL/SQL

Ssis Developer

Job description:

A SSIS developer provides support for projects like designing and maintaining metadata models and complicated ETL packages or OLAP cubes. Reporting data and converting customers' requests into sophisticated technical details are the major duties of a SSIS developer. They develop advanced BI apps using MS BI stacks like SSAS, SSIS, T-SQL, and MDX. They work with business users and other stakeholders and provide guidance to other developers.

  • Ssis Packages
  • ETL
  • SSRS
  • T-SQL
  • SQL Server Analysis
  • Database Objects

Database Tester

  • ETL
  • SQL Server
  • Regression Test Cases
  • Test Plan
  • Regression
  • Back-End

Data Warehouse Specialist

  • Data Warehouse
  • ETL
  • Data Warehousing
  • Business Intelligence
  • Architecture
  • Data Analysis

Enterprise Integration Manager

  • API
  • ETL
  • Enterprise Application Integration
  • Application Development
  • Data Integration
  • Business Process

Senior Database Developer

Job description:

Senior database developers are responsible for supporting various business intelligence and performing data evaluation activities to seize data requirements distinctly, accurately, and completely. They collaborate with a wide range of customers, including senior-level executives and reporting developers. Also, they often perform in the early stages of the software lifecycle to outline data and to design the theoretical, logical, and physical data model blueprint with suitable structure and relationships for maximum performance. Additionally, they work in a rapid environment that creates, executes, and maintains mission analytical information systems for the data warehouse community, ensuring the long-term reliability, flexibility, and sustainability of the systems.

  • ETL
  • Database Development
  • Java
  • Data Warehouse
  • PL/SQL
  • Database Design

Data Warehousing Specialist

  • Data Warehouse
  • Data Warehousing
  • ETL
  • Unix
  • Extraction
  • Business Rules

Database Developer

Job description:

A database developer specializes in designing and creating storage programs according to a client's needs. Their responsibilities revolve around meeting with clients to discuss their preferences and requirements, coordinating with other teams, identifying errors or inconsistencies by conducting regular maintenance tests, and monitoring its performance to ensure smooth workflow. A database developer may also respond to inquiries and concerns, provide corrective measures, produce instructional materials for the database users, and develop strategies to keep the data safe and secure.

  • ETL
  • C++
  • Java
  • Microsoft SQL Server
  • Database Development
  • PL/SQL

Data Warehouse Developer

Job description:

Data Warehouse Developers are information technology (IT) professionals assigned to manage company-related information or data. They are responsible for creating the company's data warehouse, where the company's data will be stored. Data warehouse developers are also expected to provide the maintenance needs related to the program.

  • ETL
  • Java
  • Hadoop
  • Data Warehouse
  • Visualization
  • Data Analysis

Database Development Project Manager

  • Microsoft SQL Server
  • PL/SQL
  • Ssis
  • ETL
  • Database Development
  • Project Management

Data Integrity Specialist

Job description:

A data integrity specialist is responsible for maintaining the safety and security of information from the company's network database and implementing preventive measures to avoid unauthorized access and illegal dissemination of data. Data integrity specialists restore lost data and upgrade the database infrastructure to ensure accurate deliverables and outputs. They also fix network issues, conduct regular maintenance, and provide network access only to those who are eligible to view data information. A data integrity specialist must have excellent communication and technical skills to resolve system gaps and prevent delays in operations.

  • ETL
  • Java
  • Data Quality
  • Customer Service
  • SQL Server
  • Customer Satisfaction

Business Owner/Engineer

Job description:

Business owners/engineers are executive professionals who work with business users to help develop business requirements. These professionals must create an approach for new financial data warehouse product development so that they can reduce complexity and mitigate implementation risk. By using Structured Query Language (SQL) and Python, these professionals must interface with data miners to extract, transform, and load data from a variety of sources. These professionals must also perform data analysis to extract actionable insights of key business drivers for the digital marketing industry.

  • Business Intelligence
  • Visualization
  • Python
  • Data Analysis
  • ETL
  • Power Bi

Data Migration Specialist

Job description:

A data migration specialist is a data entry professional specializing in processing and transferring data from one platform to another. They are in charge of performing research and analyses to establish migration plans, develop and implement data migration strategies, adhere to deadlines and project guidelines, conduct reviews and assessments to identify and solve issues, and produce progress reports. Moreover, a data migration specialist usually functions in a group setting, which requires an open and transparent communication line for successful outcomes.

  • ETL
  • SQL Server
  • Data Analysis
  • Data Extraction
  • Data Conversion
  • Master Data

Database Analyst/Developer

  • Microsoft SQL Server
  • ETL
  • Ssis
  • PL/SQL
  • Data Analysis
  • Database Design

Senior Sql/Report Developer

Job description:

A senior report developer works with a team to document reporting requirements. They develop reports using data stores and warehouses and ensure that reports are accessible to users. They also provide training to junior staff.

  • Power Bi
  • ETL
  • SSRS
  • Ssis Packages
  • T-SQL
  • Database Objects

Data Modeler

Job description:

A data modeler is responsible for designing and creating network systems and applications for efficient and secured data storage solutions. Data modelers work closely with the data management team to identify business needs and execute data modeling techniques for comprehensive analysis. They also strategize in improving existing data systems, upgrading infrastructure, and configuring information for compatibility with every business unit. A data modeler must have excellent technical skills, as well as a strong command of programming languages to modify and optimize data models for smooth navigation and access.

  • ETL
  • Data Analysis
  • Data Architecture
  • Physical Data Models
  • Data Warehouse
  • Tableau

Application Integrator

  • Application Integration
  • Architecture
  • Java
  • XML
  • ETL
  • FTP

SQL Developer

Job description:

An SQL developer is responsible for designing database systems for storing and accessing business information. SQL developers incorporate a high-level of data management and technical knowledge to ensure the safety and security of the systems, preventing unauthorized access that may put the company's reputation in jeopardy. They evaluate the network infrastructure, run multiple diagnostic tests, and update the information security systems for optimal performance and efficient navigation. An SQL developer must have excellent skills in programming languages, data engineering, and software management to handle the complexities of system commands and data validation.

  • Database Objects
  • T-SQL
  • SSRS
  • ETL
  • SQL Server Analysis
  • Java

Reports Developer

Job description:

A reports developer is primarily in charge of processing data into comprehensive reports, aiming to produce information that is accessible to different employees in a company. Among their responsibilities include coordinating with different departments to gather and analyze data, understand the needs of different offices, design reports in adherence to particular formats, and utilize systems for other resources. Furthermore, as a reports developer, it is essential to maintain an active communication line with staff for a smooth and efficient workflow.

  • BI
  • ETL
  • SSRS
  • Power Bi
  • PL/SQL
  • Visualization

Business Intelligence Developer

Job description:

A business intelligence developer is primarily responsible for organizing and developing systems that will inform the company of essential data and solutions as a basis for decision-making. They are also responsible for coordinating with stakeholders and other high-ranking personnel to determine specific goals, develop models, conduct research and analysis, and gather data through various processes, ensuring accuracy and productivity. Furthermore, as a developer, it is essential to ensure that all processes adhere to the company's standards and policies.

  • Power Bi
  • Business Intelligence
  • Analytics
  • Dashboards
  • ETL
  • Visualization

How much can you earn with ETL skills?

You can earn up to $91,441 a year with etl skills if you become a data warehouse consultant, the highest-paying job that requires etl skills. Ssis developers can earn the second-highest salary among jobs that use Python, $94,071 a year.

Job TitleAverage SalaryHourly Rate
Data Warehouse Consultant$91,441$44
Ssis Developer$94,071$45
Database Tester$91,001$44
Data Warehouse Specialist$78,418$38
Enterprise Integration Manager$127,462$61

Companies using ETL in 2025

The top companies that look for employees with etl skills are Oracle, Guidehouse, and Deloitte. In the millions of job postings we reviewed, these companies mention etl skills most frequently.

RankCompany% Of All SkillsJob Openings
1Oracle15%35,922
2Guidehouse12%1,214
3Deloitte8%26,116
4Intel7%1,716
5Lincoln Financial Group6%1,562

Departments using ETL

DepartmentAverage Salary
IT$94,287

20 courses for ETL skills

Advertising Disclosure

1. ETL for beginners: ( SSIS, SSDT ,ETL, MS-SQL Server )

udemy
4.3
(99)

A common problem that organizations face is how to gathering data from multiple sources, in multiple formats, and move it to one or more data stores. The destination may not be the same type of data store as the source, and often the format is different, or the data needs to be shaped or cleaned before loading it into its final destination. Extract, transform, and load (ETL) is a data pipeline used to collect data from various sources, transform the data according to business rules, and load it into a destination data store. SQL Server Integration Services (SSIS) is a useful  and powerful Business Intelligence Tool. It is best suited to work with SQL Server Database. It is added to SQL Server Database when you install SQL Server Data Tools  (SSDT)which adds the Business Intelligence Templates to Visual studio that is used to create Integration projects. SSIS can be used for: Data Integration Data Transformation Providing solutions to complex Business problems Updating data warehouses Cleaning data Mining data Managing SQL Server objects and data Extracting data from a variety of sources Loading data into one or several destinationsWhat You Will Learn.... How to install SQL Server Database  How to download and attach a database to SQL Server How to download and install SQL Server Data Tools How to Create a New Integration Services Project How to add and Configuring a Flat File Connection Manager How to add and Configuring an OLE DB Connection Manager How to add a Data Flow Task to the Package How to add and Configuring the Flat File Source How to add and Configuring the Lookup Transformations How to Create Integration Services Tasks How to Create  New Connection Manager How to Write data to a SQL Server database How to Execute a package from SQL Server Data Tools How to Control Data Flow for Flat Files How to test  Packages...

2. ETL Testing Interview Questions

udemy
4.2
(107)

Preparing for an interview is tricky. You would need to get a good understanding of new features and revise concepts you used in your preparation. This course helps you prepare for ETL Testing Interview with hands-on code examples covering 200+ Interview Questions and Answers on varied range of topics. Discover not just what are the interview questions, but how to answer the questions to ensure you get the job as an ETL Testing professional or Data warehouse Testing professional. All questions are dealt with in detailed explanation and narration of what happens practically and in real time. What will you learn?Understand what kind of questions are asked in ETL/DWH/BI Testing Interviews. Answer questions on Data warehouse concepts, ETL , BI and various other practical scenarios in real time projects. Understand New Features of ETL Tools. Understand Basic Testing Concepts. Understand Advanced practical DWH/ETL/BI Testing Concepts. Answer questions on Data Validations, Test Data Creation and Supporting the business in UAT. And much more.... What is required for you to start with this course?Familiarity with RDBMS Concpts and basics of ETL Testing. In the course, we use Informatica 9x/10x and Oracle 11g to demonstrate examples...

3. BI Foundations with SQL, ETL and Data Warehousing

coursera

Professionals with SQL, ETL, Enterprise Data Warehousing (EDW), Business Intelligence (BI) and Data Analysis skills are in great demand. This Specialization is designed to provide career relevant knowledge and skills for anyone wanting to pursue a job role in domains such as Data Engineering, Data Management, BI or Data Analytics. The program consists of four online courses. In the first course you learn the basics of SQL and how to query relational databases with this powerful language. Next you learn to use essential Linux commands and create basic shell scripts. You continue your journey by learning to build and automate ETL, ELT and data pipelines using BASH scripts, Apache Airflow and Apache Kafka. In the final course you learn about Data Lakes, Data Marts as well as work with Data Warehouses. You also create interactive reports and dashboards to derive insights from data in your warehouse. Note that this specialization has a significant emphasis on hands-on practice employing real tools used by data professionals. Every course has numerous hands-on labs as well as a course project. While you will benefit from some prior programming experience, it is not absolutely necessary for this course. The only pre-requisites for this specialization are basic computer and data literacy, and a passion to self-learn online...

4. ETL Testing: From Beginner to Expert

udemy
4.1
(2,223)

DW/BI/ETL Testing Training Course is designed for both entry-level and advanced Programmers. The course includes topics related to the foundation of  Data Warehouse with the concepts, Dimensional Modeling and important aspects of Dimensions, Facts and Slowly Changing Dimensions along with the DW/BI/ETL set up,  Database Testing Vs Data Warehouse Testing, Data Warehouse Workflow and Case Study, Data Checks using SQL, Scope of BI testing and as a bonus you will also get the steps to set up the environment with the most popular ETL tool Informatica to perform all the activities on your personal computer to get first hand practical knowledge...

5. Professional Informatica Power Center ETL Course

udemy
4.4
(297)

Hello Candidates, If you are looking to get skilled in Informatica Power center ETL tool, then you are at the right place. If you are a Beginner, Fresher or an experience candidate who is willing to learn Informatica Power Center ETL for a Developer role, then this course provides you the required knowledge and hands on experience with real time scenarios explained and implemented in a very structured manner. Total course duration is 31+ hours where every single concept is explained practically with real time examples, which will give confidence to candidates when they get into an interview or when they work on a real time Infromatica project. The Course starts with Intro, covering every transformations, basic and advance features. The Course also contains very useful Interview material which can help you in clearing interviews. It also includes documents on Database, SQL, PLSQL and UNIX where important topics are covered which help you in interviews. Post the course, you can confidently clear any Informatica interviews or work on any real time Informatica projects subjected you have practiced each and every concept explained here. Prerequisite for the Course: Basics of Database. Keen to learn most popular ETL tool in IT marketTools Used: Oracle 11g Xpress EditionSQL DeveloperInformatica Power Center 9.6.1...

6. ETL Framework for Data Warehouse Environments

udemy
3.9
(594)

This course provides a high level approach to implement an ETL framework in any typical Data Warehouse environments. The practical approaches can be used for a new application that needs to design and implement ETL solution which is highly reusable with different data loading strategies, error/exception handling, audit balance and control handling, a bit of job scheduling and the restartability features and also to any existing ETL implementations. For existing implementations this framework needs to be embedded into the existing environment, jobs and business requirements and it might also go to a level of redesigning the whole mapping/mapplets and the workflows (ETL jobs) from scratch, which is definitely a good decision considering the benefits for the environment with high re-usability and improved design standards.  This course is a combination of standard and practical approaches of designing and implementing a complete ETL solution which details the guidelines, standards, developer/architect checklist and the benefits of the reusable code. And, this course also teaches you the Best practices and standards to be followed in implementing ETL solution.  Though this course, covers the ETL design principles and solutions based on Informatica 10x, Oracle 11g, these can be incorporated to any of the ETL tools in the market like IBM DataStage, Pentaho, Talend, Ab-intio etc.  Multiple reusable code bundles from the marketplace, checklists and the material required to get started on UNIX for basic commands and Shell Scripting will be provided...

7. SQL/ETL Developer - T-SQL/Stored Procedures/ETL/SSIS

udemy
4.2
(226)

A common problem that organizations face is how to gathering data from multiple sources, in multiple formats, and move it to one or more data stores. The destination may not be the same type of data store as the source, and often the format is different, or the data needs to be shaped or cleaned before loading it into its final destination. Extract, transform, and load (ETL) is a data pipeline used to collect data from various sources, transform the data according to business rules, and load it into a destination data store. SQL Server Integration Services (SSIS) is a useful  and powerful Business Intelligence Tool. It is best suited to work with SQL Server Database. It is added to SQL Server Database when you install SQL Server Data Tools  (SSDT)which adds the Business Intelligence Templates to Visual studio that is used to create Integration projects. SSIS can be used for: Data Integration Data Transformation Providing solutions to complex Business problems Updating data warehouses Cleaning data Mining data Managing SQL Server objects and data Extracting data from a variety of sources Loading data into one or several destinationsWhat You Will Learn.... How to install SQL Server Database  How to download and attach a database to SQL Server How to download and install SQL Server Data Tools How to Create a New Integration Services Project How to add and Configuring a Flat File Connection Manager How to add and Configuring an OLE DB Connection Manager How to add a Data Flow Task to the Package How to add and Configuring the Flat File Source How to add and Configuring the Lookup Transformations How to Create Integration Services Tasks How to Create  New Connection Manager How to Write data to a SQL Server database How to Execute a package from SQL Server Data Tools How to Control Data Flow for Flat Files How to test  Packages SQL FunctionsT-SQL Stored proceduresExtracting data from multiple tables...

8. ETL and Data Pipelines with Shell, Airflow and Kafka

coursera

Delve into the two different approaches to converting raw data into analytics-ready data. One approach is the Extract, Transform, Load (ETL) process. The other contrasting approach is the Extract, Load, and Transform (ELT) process. ETL processes apply to data warehouses and data marts. ELT processes apply to data lakes, where the data is transformed on demand by the requesting/calling application. In this course, you will learn about the different tools and techniques that are used with ETL and Data pipelines. Both ETL and ELT extract data from source systems, move the data through the data pipeline, and store the data in destination systems. During this course, you will experience how ELT and ETL processing differ and identify use cases for both. You will identify methods and tools used for extracting the data, merging extracted data either logically or physically, and for loading data into data repositories. You will also define transformations to apply to source data to make the data credible, contextual, and accessible to data users. You will be able to outline some of the multiple methods for loading data into the destination system, verifying data quality, monitoring load failures, and the use of recovery mechanisms in case of failure. By the end of this course, you will also know how to use Apache Airflow to build data pipelines as well be knowledgeable about the advantages of using this approach. You will also learn how to use Apache Kafka to build streaming pipelines as well as the core components of Kafka which include: brokers, topics, partitions, replications, producers, and consumers. Finally, you will complete a shareable final project that enables you to demonstrate the skills you acquired in each module...

9. ETL using Python: from MySQL to BigQuery

udemy
4
(215)

This is a direct and to the point course that will get you quickly ETL'ing data from MySQL to BigQuery. The lessons in this course are broken out into short How-Tos. Therefore you can take this course over the weekend and be ready to show off your skills on Monday morning! Things that we will cover: SetupSetting up a GCP AccountCredential and Authentication for securityPython Environment SetupExtractUse Python to connect to MySQLUse Python's pandas to export dataPython library usage for saving files to file pathsTransformUse Python functions to transform dataUse Python pandas to transform dataUse inline SQL during Extract for data transformationLoadUse the BigQuery Python libraryConnect to BigQueryLoad data to BigQueryIncremental Loads vs Truncate and LoadOther data handling options during LoadAfter taking this course, you'll be comfortable with the following pretty cool things: Connect to MySQL using PythonLearn how to obscure your database credentials so you're not exposing them in your codeUsage of the os module for the purpose of saving files and hard coding fewer things. Use both Python and the pandas library to transform data on the fly during the Transformation phase of your ETLLearn how to use GBQ's modules/libraries to make the loading of the data a very easy, straightforward taskHave fun, enjoy and keep growing!...

10. Talend ETL Data warehousing SQL Beginner to Experts

udemy
4.9
(60)

Talend ETL Data warehousing SQL  Beginner to Experts Topics Datawarehousing Concepts ETL Concepts tsortrow, tunite, tuniqerow, tbufferinput, tbuffer, output, thashinput, thashoutput, tfilelist, tsleep, tloop, file, input, output, components, database, input, output, components, tsendmail, treplicate, tfiltercolumns, tfilterrows, treplace, tconverttype, tdie, tcontextload, trowgenerator, trunjob, prejob, postjob, tsamplerows, tnormalize, tdenormalize, tmap, taggrigator, tjoin, tsystem, tjava, tjavarow, tjavaflex, tschemacompliancecheck, tlogrow, tlogcatcher, t, statcatcher, tfilecopy, tfilearchive, tfileProperties, tfileunarchive, tfiletouch, tfiledelete, tfileexist, tftpfilelist, tftpput, tftpget, tftpdelete, tftpfileexist, tftpConnection, tftpRename, tftpfileproperties, toracleInput, toraclerow, toracleoutpt, toracleconnection, toracleoutputBulkexec, toracleBulkexec, toracleClose, toracleRollback, toraclecommit, tmssqlInput, tmssqlrow, tmssqloutpt, tmssqlconnection, tmssqlBulk, tmssqlBulkexec, tmssqlClose, tmssqlRollback, tmssqlcommit, tDb2Input, tDb2row, tDb2outpt, tDb2connection, tDb2Bulk, tDb2Bulkexec, tDb2Close, tDb2Rollback, tDb2commit, OnsubJobOK, OnSubjobError, OnComponentOk, OnComponentError, runif, tExcelInput, tExceloutput, tfileInputjson, tfileoutputjson, tfileInputXml, tfileoutputXml, tfileinputPositional, tfileOutputPositional, SCD1, SCD2, SCD3, stage loading Dimension Loading fact Loading project Explanation , flow to iterate , iterate to flow, tsortrow, tunite, tuniqerow, tbufferinput, tbuffer, output, thashinput, thashoutput, tfilelist, tsleep, tloop, file, input, output, components, database, input, output, components, tsendmail, treplicate, tfiltercolumns, tfilterrows, treplace, tconverttype, tdie, tcontextload, trowgenerator, trunjob, prejob, postjob, tsamplerows, tnormalize, tdenormalize, tmap, taggrigator, tjoin, tsystem, tjava, tjavarow, tjavaflex, tschemacompliancecheck, tlogrow, tlogcatcher, t, statcatcher, tfilecopy, tfilearchive, tfileProperties, tfileunarchive, tfiletouch, tfiledelete, tfileexist, tftpfilelist, tftpput, tftpget, tftpdelete, tftpfileexist, tftpConnection, tftpRename, tftpfileproperties, toracleInput, toraclerow, toracleoutpt, toracleconnection, toracleoutputBulkexec, toracleBulkexec, toracleClose, toracleRollback, toraclecommit, tmssqlInput, tmssqlrow, tmssqloutpt, tmssqlconnection, tmssqlBulk, tmssqlBulkexec, tmssqlClose, tmssqlRollback, tmssqlcommit, tDb2Input, tDb2row, tDb2outpt, tDb2connection, tDb2Bulk, tDb2Bulkexec, tDb2Close, tDb2Rollback, tDb2commit, OnsubJobOK, OnSubjobError, OnComponentOk, OnComponentError, runif, tExcelInput, tExceloutput, tfileInputjson, tfileoutputjson, tfileInputXml, tfileoutputXml, tfileinputPositional, tfileOutputPositional, SCD1, SCD2, SCD3, stage loading Dimension Loading fact Loading project Explanation , flow to iterate , iterate to flow, tsortrow, tunite, tuniqerow, tbufferinput, tbuffer, output, thashinput, thashoutput, tfilelist, tsleep, tloop, file, input, output, components, database, input, output, components, tsendmail, treplicate, tfiltercolumns, tfilterrows, treplace, tconverttype, tdie, tcontextload, trowgenerator, trunjob, prejob, postjob, tsamplerows, tnormalize, tdenormalize, tmap, taggrigator, tjoin, tsystem, tjava, tjavarow, tjavaflex, tschemacompliancecheck, tlogrow, tlogcatcher, t, statcatcher, tfilecopy, tfilearchive, tfileProperties, tfileunarchive, tfiletouch, tfiledelete, tfileexist, tftpfilelist, tftpput, tftpget, tftpdelete, tftpfileexist, tftpConnection, tftpRename, tftpfileproperties, toracleInput, toraclerow, toracleoutpt, toracleconnection, toracleoutputBulkexec, toracleBulkexec, toracleClose, toracleRollback, toraclecommit, tmssqlInput, tmssqlrow, tmssqloutpt, tmssqlconnection, tmssqlBulk, tmssqlBulkexec, tmssqlClose, tmssqlRollback, tmssqlcommit, tDb2Input, tDb2row, tDb2outpt, tDb2connection, tDb2Bulk, tDb2Bulkexec, tDb2Close, tDb2Rollback, tDb2commit, OnsubJobOK, OnSubjobError, OnComponentOk, OnComponentError, runif, tExcelInput, tExceloutput, tfileInputjson, tfileoutputjson, tfileInputXml, tfileoutputXml, tfileinputPositional, tfileOutputPositional, SCD1, SCD2, SCD3, stage loading Dimension Loading fact Loading project Explanation , flow to iterate , iterate to flow...

11. Data Engineering, Serverless ETL & BI on Amazon Cloud

udemy
4.3
(711)

AWS Cloud can seem intimidating and overwhelming to a lot of people due to its vast ecosystem, but this course will make it easier for anyone who wants a hands-on expertise in setting up a data-warehouse in Redshift or setup a BI infrastructure from scratch. Data Scientists/Analysts/Business Analysts will soon be expected to (if not already) become all-rounders and handle the technical aspect of data ingestion/engineering/warehousing. Anyone who has the basic understanding of how cloud works can benefit from this course because: - This course is designed keeping in mind end to end life cycle of a typical data engineering project -  Provides a practical solution to real-world use-cases This Course covers:  Setting up a data warehouse in AWS Redshift from scratch Basic Data Warehousing Concepts Writing server-less AWS Glue Jobs (pyspark and python shell) for ETL and batch processing AWS Athena for ad-hoc analysis (when to use Athena) AWS Data Pipeline to sync incremental data Lambda functions to trigger and automate ETL/Data Syncing processes QuickSight Setup , Analyses and Dashboards Prerequisites for this course are: Python / Sql (Absolute must)PySpark (should know how to write some basic Pyspark scripts)Willingness to explore , learn and put in the extra effort to succeed An active AWS Account Important Note - This course makes use of the free tiers for Redshift and RDS , so you will not be billed for them unless you exceed the free tier usage which should be more than enough to get enough practice from this course . Also , this course makes use of AWS UI on the browser for creating clusters and setting up jobs , there is no bash scripting involved. One can use any operating system to perform the lab sessions in this course.  This course is not code-intense or code-heavy , there is only 35% coding involved , the rest is execution, understanding and chaining different component together. The whole purpose of this course is to make everyone aware of and feel comfortable with all the tools/features used in this course. Some Tips: Try to watch the videos at 1.2X speed Every time you work on a new component or feature , do some research on the other tools that are meant for the same purpose and see how they differ and in what aspects , For Eg  Redshift/Athena vs  Snowflake or Bigquery , QuickSight vs PowerBi vs Microstrategy...

12. Learn AWS Glue Build ServerLess ETL on AWS

udemy
4.2
(100)

In this course student will learn what is AWS Glue , Components, Preparation for AWS Glue , Glue Architecture, Benefits And Limitations Of AWS Glue & AWS Glue Terminology. In Section 2 Student will learn what is crawler, data catalog, Data base, tables and Practical demo of S3 Crawler, MYSQL Crawler, JSON Crawler & Build Custom Classifier. You'll learn how to set up a Glue data crawler, then how to crawl the data in a S3 folder to populate the Glue Data Catalog with metadata about the S3 data. In Section 3: You will learn about Development Endpoint, Setup endpoint, Glue Context & Dynamic Frame, How to create dynamic frame using RDD. In Section 4: You will learn about Transformation, Resolve Choice, Split Rows, Map , Filter, Select & Rename, Spigot, Flatten using JSON, Drop. In Section 5: you will learn about JOB & create trigger. How you can setup JOB on regular interval. Future topics: In Future I add add more content on Workflow, How to build incremental data pipeline using Bookmark, What is Glue Studio & What is AWS Data brew. This course is more focused on Practical example & Student will be able to work on AWS Glue project. Student will learn how to design Data pipeline...

13. Alteryx Masterclass for Data Analytics, ETL and Reporting

udemy
4.5
(846)

5 Reasons why you should choose this Alteryx courseCarefully designed curriculum teaching you only the most used functionalities of Alteryx in business environmentConcise - you can complete this Alteryx designer core certification course within one weekendBusiness related examples and case studies for learning Alteryx and becoming an Alteryx designerDownloadable resources on AlteryxYour queries will be responded by the Instructor himselfA Verifiable Certificate of Completion is presented to all students who undertake this Alteryx course. Why should you choose this course?This is a complete tutorial on Alteryx which can be completed within a weekend. Data Analysis and Analytics process automation are the most sought-after skills for Data analysis roles in all the companies. Alteryx designer core certification portrays one of the most desired skills in the market. So whether you want to start a career as a data scientist or just grow you data analysis skills, or just want to learn Alteryx or take Alteryx designer core certification, this course will cover everything you need to know to do that. Why Alteryx for Data Analysis and Analytics process automation?Alteryx is the leader in data blending and advanced analytics software. Alteryx Analytics provides analysts with an intuitive workflow for data blending and advanced analytics that leads to deeper insights in hours, not the weeks typical of traditional approaches. Alteryx makes it easy to incorporate statistical, predictive and spatial analysis in the same workflow environment with over 60 pre-built tools- and you don't have to write a single line of code. What makes us qualified to teach you?The course is taught by Abhishek and Pukhraj. Instructors of the course have been teaching Data Science and Machine Learning for over a decade. We have an in-depth understanding on and practical exposure to Alteryx. We are also the creators of some of the most popular online courses - with over a million enrollments and thousands of 5-star reviews like these ones: I had an awesome moment taking this course. It broaden my knowledge more on the power use of Excel as an analytical tools. Kudos to the instructor! - SikiruVery insightful, learning very nifty tricks and enough detail to make it stick in your mind. - ArmandOur PromiseTeaching our students is our job and we are committed to it. If you have any questions about the course content, Alteryx, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message. By the end of this course, your confidence in using Alteryx will soar. You'll have a thorough understanding of how to use Alteryx for study or as a career opportunity. Go ahead and click the enroll button, and I'll see you in lesson 1 of this Alteryx course! CheersStart-Tech AcademyFAQsWhat type of software is Alteryx?Alteryx Designer is a Windows software application that provides an intuitive drag-and- drop user interface for users to create repeatable workflow processes. Users can drag tools from a toolbox onto a canvas, connect them together, and edit their properties to create Alteryx workflows, apps, and macrosWhat is analytic process automation?Analytic Process Automation (APA) is the technology that allows anyone in your organization to easily share data, automate tedious and complex processes, and turn data into results. With Analytic Process Automation, anyone can unlock predictive and prescriptive insights that drive quick wins and fast ROI. How expensive is Alteryx?We get one month free trial for Alteryx and we suggest that students complete the course within this trial period. Otherwise, Alteryx Designer - Alteryx's desktop-based, design-time platform costs $5,195 per year, per user under a one-year contract. What is ETL?The ETL (extract, transform, load) process is the most popular method of collecting data from multiple sources and loading it into a centralized data warehouse. ETL is an essential component of data warehousing and analytics. How much can I earn?In the US, median salary of an Analytics process developer is $74,835 and in India average salary is Rs. 7,06,902 per year. Accenture, Tata Consultancy Services, Cognizant Technology Solutions, Capgemini, IBM, Infosys etc. are major recruiters for people skilled in Analytics Automation tools...

14. Mastering Databricks & Apache spark -Build ETL data pipeline

udemy
4
(409)

Welcome to the course on Mastering Databricks & Apache spark -Build ETL data pipelineDatabricks combines the best of data warehouses and data lakes into a lakehouse architecture. In this course we will be learning how to perform various operations in Scala, Python and Spark SQL. This will help every student in building solutions which will create value and mindset to build batch process in any of the language. This course will help in writing same commands in different language and based on your client needs we can adopt and deliver world class solution. We will be building end to end solution in azure databricks. Key Learning PointsWe will be building our own cluster which will process our data and with one click operation we will load different sources data to Azure SQL and Delta tablesAfter that we will be leveraging databricks notebook to prepare dashboard to answer business questionsBased on the needs we will be deploying infrastructure on Azure cloudThese scenarios will give student 360 degree exposure on cloud platform and how to step up various resourcesAll activities are performed in Azure DatabricksFundamentalsDatabricksDelta tablesConcept of versions and vacuum on delta tablesApache Spark SQLFiltering DataframeRenaming, drop, Select, CastAggregation operations SUM, AVERAGE, MAX, MINRank, Row Number, Dense RankBuilding dashboardsAnalyticsThis course is suitable for Data engineers, BI architect, Data Analyst, ETL developer, BI Manager...

15. ETL Testing: Basic course for all QA professionals 2023

udemy
4.1
(51)

DW/BI/ETL Testing Training Course is designed for both entry-level and advanced software Manual testers. The course includes topics related to the foundation of Data Warehouse with the concepts,  Database Testing Vs Data Warehouse Testing, Data Warehouse Workflow, How to perform ETL Testing, ETL Testing Basic Concepts,  Data Checks using SQL, Scope of BI/ETL  testing and as an extra, you will also get the steps to run SQL Queries, ETL tools Scope specified in details for data manipulation, data cleaning, Data Transformation industry best practices. In this course you will learn the complete RoadMap what you need to learn to become a ETL Tester. Lots of People perform ETL Data validations with the help of Mapping sheets or simply perform data migration testing. But in ETL you can now perform without manual testing effort if you knows about Ms. Excel Advance features like conditional formatting, Power Query, Power BI, SQL Advance level. Then ETL Field is waiting for you. In this course following below topics covered with Real time examples:1. Introduction to Data warehouse2. Introduction to Power Query3. RoadMap how to become a ETL Testers4. How much time requires to become a ETL Tester5. Tools & Techniques how to become a ETL Tester...

16. Learn to master ETL data integration with Pentaho kettle PDI

udemy
4.3
(278)

Pentaho kettle Development course with Pentaho 8 - 08-2019 #1Learn how to Develop real pentaho kettle projectsGet a lot of tips and tricks. Become master in transformation steps and jobsKnow how to set Pentaho kettle environmentBe familiar with the most used steps of Pentaho kettleSolve issuesStart making money as an ETL developerWhat is the target audience?SQL developers, ETL developers, code developers (Python, PHP...), Automation developers, BI developers, software project managers and anyone who like to understand what is ETLthe Pentaho kettle course is meant for people who have some background with SQL syntax, Queries, and database design, you don't need to be expert on that, I will guide you throughin case you don't know SQL at all, I suggest you take a course-specific for that before you enroll in this coursethis course is only for students who are serious in working hands-on, practice and some more practice. it is not reading or watching. you will be an expert but only if you try everything I show by your self...

17. Data Analyst - ETL/SSIS/SQL/PowerBI

udemy
4.2
(350)

Data analysts are in high demand across all sectors, such as finance, consulting, manufacturing, pharmaceuticals, government and education. The ability to pay attention to detail, communicate well and be highly organised are essential skills for data analysts. They not only need to understand the data, but be able to provide insight and analysis through clear visual, written and verbal communication. A common problem that organizations face is how to gathering data from multiple sources, in multiple formats, and move it to one or more data stores. The destination may not be the same type of data store as the source, and often the format is different, or the data needs to be shaped or cleaned before loading it into its final destination. Extract, transform, and load (ETL) is a data pipeline used to collect data from various sources, transform the data according to business rules, and load it into a destination data store. SQL Server Integration Services (SSIS) is a useful  and powerful Business Intelligence Tool. It is best suited to work with SQL Server Database. It is added to SQL Server Database when you install SQL Server Data Tools  (SSDT)which adds the Business Intelligence Templates to Visual studio that is used to create Integration projects. SSIS can be used for: Data Integration Data Transformation Providing solutions to complex Business problems Updating data warehouses Cleaning data Mining data Managing SQL Server objects and data Extracting data from a variety of sources Loading data into one or several destinationsSQL is a standard language for accessing and manipulating databases. SQL stands for Structured Query LanguageWhat Can SQL do?SQL can execute queries against a databaseSQL can retrieve data from a databaseSQL can insert records in a databaseSQL can update records in a databaseSQL can delete records from a databaseSQL can create new databasesSQL can create new tables in a databaseSQL can create stored procedures in a databaseSQL can create views in a databaseSQL can set permissions on tables, procedures, and viewsPower BI is a business analytics solution that lets you visualize your data and share insights across your organization, or embed them in your app or website. Connect to hundreds of data sources and bring your data to life with live dashboards and reports. Discover how to quickly glean insights from your data using Power BI. This formidable set of business analytics tools-which includes the Power BI service, Power BI Desktop, and Power BI Mobile-can help you more effectively create and share impactful visualizations with others in your organization. In this  course you will learn how to  get started with this powerful toolset.  We will  cover topics like  connecting to and transforming web based data sources.  You will learn how to publish and share your reports and visuals on the Power BI service...

18. Writing production-ready ETL pipelines in Python / Pandas

udemy
4.1
(678)

This course will show each step to write an ETL pipeline in Python from scratch to production using the necessary tools such as Python 3.9, Jupyter Notebook, Git and Github, Visual Studio Code, Docker and Docker Hub and the Python packages Pandas, boto3, pyyaml, awscli, jupyter, pylint, moto, coverage and the memory-profiler. Two different approaches how to code in the Data Engineering field will be introduced and applied - functional and object oriented programming. Best practices in developing Python code will be introduced and applied: design principlesclean codingvirtual environmentsproject/folder setupconfigurationloggingexeption handlinglintingdependency managementperformance tuning with profilingunit testingintegration testingdockerizationWhat is the goal of this course?In the course we are going to use the Xetra dataset. Xetra stands for Exchange Electronic Trading and it is the trading platform of the Deutsche Börse Group. This dataset is derived near-time on a minute-by-minute basis from Deutsche Börse's trading system and saved in an AWS S3 bucket available to the public for free. The ETL Pipeline we are going to create will extract the Xetra dataset from the AWS S3 source bucket on a scheduled basis, create a report using transformations and load the transformed data to another AWS S3 target bucket. The pipeline will be written in a way that it can be deployed easily to almost any production environment that can handle containerized applications. The production environment we are going to write the ETL pipeline for consists of a GitHub Code repository, a DockerHub Image Repository, an execution platform such as Kubernetes and an Orchestration tool such as the container-native Kubernetes workflow engine Argo Workflows or Apache Airflow. So what can you expect in the course?You will receive primarily practical interactive lessons where you have to code and implement the pipeline and theory lessons when needed. Furthermore you will get the python code for each lesson in the course material, the whole project on GitHub and the ready to use docker image with the application code on Docker Hub. There will be power point slides for download for each theoretical lesson and useful links for each topic and step where you find more information and can even dive deeper...

19. Data Integration & ETL with Talend Open Studio Zero to Hero

udemy
4.6
(1,056)

Data. Everywhere. All well-behaved in their own environment. But who actually lets them talk to each other? You do. With data integration. Become a data savant and add value with ETL and your new knowledge! Talend Open Studio is an open, flexible data integration solution. You build your processes with a graphical editor and over 600 components provide flexibility. Each section has a practical example and you will receive this complete material at the beginning of the course. So you can not only view each section, but also compare it to your own solution. There are also extensive practical scenarios included. So you'll be well equipped for practice! What are the biggest topics you can expect?Installation on different operating systems (Windows, Linux, Mac)understanding and using important data typesreading and writing from databasesprocess different file formats, like Excel, XML, JSON, delimited, positionalcreate and use metadatabuild schemasuse helpful keyboard shortcutsretrieve data from WebServices / RESTconnect to GoogleDrive and fetch datausing iteration and loopsconvert data flows into iterationsbuild and understand job hierarchiesAll major transformations: Map, join, normalize, pivot, and aggregate datacreate and extract XML and JSONuse regular expressionsOrchestrate components in processesCheck and improve data qualityUse fuzzy matching and interval matchingUse variables for different environmentsPerform schema validationHandle reject data separatelyFind and fix errors quicklyWrite meaningful logsInclude and react to warnings and abortsBuild job hierarchies and pass data between different levelsimplement and test your own assumptionsconfigure your project for logging, versioning and context loadinglearn best practices and establish your owndocument items and have documentation generatedWhat are you waiting for? See you in the course!...

20. Apache NiFi Complete Master Course - HDP - Automation ETL

udemy
4.7
(916)

Apache Nifi is next generation framework to create data pipeline and integrate with almost all popular systems in the enterprise. It has more than 250 processors and more than 70 controllers. This course covers all all basic to advanced concepts available in Apache Nifi likeFlowfileControllersProcessorsConnectionsProcess GroupFunnelData ProvenanceProcessor relationshipsInput and Output PortsThis course also covers on the Apache Nifi Subprojects like Nifi RegistryAs part of production maintenance, user may have to take cautious decision to improve the performance and handle the errors efficiently. To facilitate the same, Demo also covers on Handling Throughput and LatencyHandling Back Pressure and YieldError handlingFailure RetryMonitoring BulletinData ProvenanceTo have seamless experience with data, handling of data latency and throughput and prioritizing the data is important. Its controlled with relationship, yield and back pressure. Various processors and controllers to process various type of data is demonstrated. Processors which are used in production scenarios like HTTP, RDBMS, NoSQL S3, CSV, JSON, Hive, etc., are covered in detail along with controllers like SSL, ConnectionPool, etc., with demo. All these concepts are covered with demo and real time implementation is provided. For easy practical purpose, all the demonstrated flowfile template is uploaded as part of the course. Demo on creating and using KeyStore, Trust Store for SSL communication. Using Maven and Eclipse EE for custom processor and deploying nar file to Nifi libraries...