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Data architect skills for your resume and career

Updated January 8, 2025
4 min read
Quoted experts
Randall Randall,
Pavel Chernyavskiy Ph.D.
Data architect example skills
Below we've compiled a list of the most critical data architect skills. We ranked the top skills for data architects based on the percentage of resumes they appeared on. For example, 8.6% of data architect resumes contained analytics as a skill. Continue reading to find out what skills a data architect needs to be successful in the workplace.

15 data architect skills for your resume and career

1. Analytics

Here's how data architects use analytics:
  • Designed the Global Program Dashboard, a module providing high-level client aggregations and analytics with support for conformed foreign currency presentation.
  • Played technical leadership role on building automated, data-driven analytics solutions to support enterprise BI transformation and decision making.

2. Architecture

Here's how data architects use architecture:
  • Provided End-to-End Business solution driven architecture for Data Integration across heterogeneous environment using Golden Gate and got rid of AQ mechanisms.
  • Collaborated with Enterprise Architecture and Business Architecture teams to develop rigorous methods and standards for business process and data architecture modeling.

3. Java

Java is a widely-known programming language that was invented in 1995 and is owned by Oracle. It is a server-side language that was created to let app developers "write once, run anywhere". It is easy and simple to learn and use and is powerful, fast, and secure. This object-oriented programming language lets the code be reused that automatically lowers the development cost. Java is specially used for android apps, web and application servers, games, database connections, etc. This programming language is closely related to C++ making it easier for the users to switch between the two.

Here's how data architects use java:
  • Developed Java based data application for major automated database conversions.
  • Developed in Java with PostgresSQL High Availability database platform.

4. Data Lake

Here's how data architects use data lake:
  • Push data from flat file sources (can be external and internal) to data lake (Hadoop environment).
  • Worked with Data Lake, Spark, AWS Redshift.

5. AWS

Here's how data architects use aws:
  • Used AWS (Amazon Web Services) Cloud computing EC2 for provisioning like new instance (VM) creation.
  • Worked with Amazon Web Services (AWS) and involved in ETL, Data Integration and Migration.

6. Hadoop

Hadoop is an open-source software and procedures framework that is free for anyone to use on the internet. Hadoop aids in big data operations. It allows massive data storage, applications to be run on commodity hardware, and can easily manage to run various tasks occurring at the same time.

Here's how data architects use hadoop:
  • Deployed and monitored jobs and applications running on Hadoop clusters for making continuous improvement to existing architecture.
  • Participated on a work effort to analyze the Hadoop ecosystem in a virtual emerging technology environment.

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7. Python

Python is a widely-known programming language. It is an object-oriented and all-purpose, coding language that can be used for software development as well as web development.

Here's how data architects use python:
  • Increased programming exposure alongside engineers and plotted latency performance plots using python.
  • Develop python scripts to ingest and process data delivered from the finance team.

8. Data Quality

Here's how data architects use data quality:
  • Performed analysis of requirements, data sources and data quality to produce overall design and implementation of the enterprise data warehouses.
  • Contributed and enforced data governance policy, data quality and data integrity policy, and data movement and data integration policy.

9. ETL

Here's how data architects use etl:
  • Provided database engineering/data architect expertise on analyzing data usage, database object utilization/implementation, and ETL process.
  • Provided data integration scheduling, exception management, event notification and ETL operational reporting and audit services.

10. NoSQL

Here's how data architects use nosql:
  • Designed a high speed proprietary NoSQL engine to serve as distributed cache within map-reduce.
  • Involved in NoSQL database vendor selections and expertise with Cassandra and MongoDB.

11. Visualization

Here's how data architects use visualization:
  • Exported the analyzed data to the relational databases using HIVE for visualization and to generate reports for the BI team.
  • Participated in creating documentation for presenting Data, data findings, Machine learning results and visualization of the findings.

12. Data Governance

Data governance is an assortment of cycles, jobs, arrangements, principles, and measurements that guarantee the successful and productive utilization of data in empowering an association to accomplish its objectives. Information administration characterizes who can make a what move, upon what information, in what circumstances, utilizing what strategies

Here's how data architects use data governance:
  • Implement and maintain Enterprise Information Management processes: Data Stewardship, Data Governance, Metadata Management, Master Data Management.
  • Conducted Structured Review sessions to reconcile model updates and related work with Senior Data Architects and Data Governance/Data Architecture Manager.

13. Azure

Here's how data architects use azure:
  • Key person for the overall systems design and the Microsoft Azure PaaS Application development.
  • Presented Demo on Microsoft Azure, an overview of cloud computing with Azure.

14. Data Warehouse

Data warehouse, often abbreviated as either DW or DWH is a system used in computing for data analysis as well reporting. The DW is also considered to be an integral component of business intelligence as they also provide storage facilities for both real-time and historical data. ETL and ELT are the two driving forces behind a data warehouse system.

Here's how data architects use data warehouse:
  • Performed gap analysis between the current state and future data warehouse environment identifying data gaps and quality issues recommended potential solutions.
  • Coordinated senior management and key internal stakeholders in determining business requirements for a fixed asset repository stored in the data warehouse.

15. Power Bi

Here's how data architects use power bi:
  • Create reports in Power BI preview portal utilizing the SSAS Tabular via Analysis connector.
  • Design and Developed OLAP cubes using SSAS 2012 and Reports using SSRS 2012 and Power BI Designer for various business modules.
top-skills

What skills help Data Architects find jobs?

Tell us what job you are looking for, we’ll show you what skills employers want.

What skills stand out on data architect resumes?

Randall Randall

Program Head Architecture, Professor, University of Idaho

Diversity of creative work demonstrated in a portfolio.

What data architect skills would you recommend for someone trying to advance their career?

Pavel Chernyavskiy Ph.D.

Assistant Professor of Statistics, University of Wyoming

Statisticians with subject-matter expertise tend to be more in-demand, all else being equal. For example, quantitative biologists, statistical geneticists, bioinformaticians, industrial statisticians can all be thought of as "statisticians with subject-matter expertise," at least in my opinion. With that in mind, if an applicant can develop their knowledge of a particular area of application during their gap year, it should help them in the job market.

What type of skills will young data architects need?

Zhixin Wu Ph.D.Zhixin Wu Ph.D. LinkedIn profile

Associate Professor, DePauw University

Problem solving skills, analytical skills, self-learning ability, and good communication skills.
Do you want to know more?
Read more about what experts have to say about data architect

List of data architect skills to add to your resume

Data architect skills

The most important skills for a data architect resume and required skills for a data architect to have include:

  • Analytics
  • Architecture
  • Java
  • Data Lake
  • AWS
  • Hadoop
  • Python
  • Data Quality
  • ETL
  • NoSQL
  • Visualization
  • Data Governance
  • Azure
  • Data Warehouse
  • Power Bi
  • BI
  • Tableau
  • Kafka
  • Data Integration
  • Data Warehousing
  • Emerging Technologies
  • Client Facing
  • Data Analysis
  • SQL Server
  • Metadata
  • Amazon Web Services
  • HBase
  • Cloud Computing
  • Data Structures
  • MDM
  • Informatica
  • HDFS
  • XML
  • Ssis
  • Physical Data Models
  • MapReduce
  • Database Design
  • PL/SQL
  • Sqoop
  • Snowflake
  • Prototyping
  • Teradata
  • Data Dictionary
  • Leveraged
  • Profiling
  • Flume
  • Linux

Updated January 8, 2025

Zippia Research Team
Zippia Team

Editorial Staff

The Zippia Research Team has spent countless hours reviewing resumes, job postings, and government data to determine what goes into getting a job in each phase of life. Professional writers and data scientists comprise the Zippia Research Team.

Updated January 8, 2025

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