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Senior data analyst- skills for your resume and career

Updated January 8, 2025

5 min read

Quoted experts

David Feldman Ph.D.,

Pavel Chernyavskiy Ph.D.

Below we've compiled a list of the most critical senior data analyst- skills. We ranked the top skills for senior data analysts based on the percentage of resumes they appeared on. For example, 10.7% of senior data analyst- resumes contained data analysis as a skill. Continue reading to find out what skills a senior data analyst- needs to be successful in the workplace.

15 senior data analyst- skills for your resume and career

1. Data Analysis

Here's how senior data analysts use data analysis:

Performed Participating/Non-participating provider data analysis.
Worked with internal technical teams, performed data analysis and assessment for successful implementation of data correction in the data warehouse.

2. Power Bi

Here's how senior data analysts use power bi:

Create reports in Power BI preview portal utilizing the SSAS Tabular via Analysis connector.
Created multiple data visualization solution for initial Power BI business preview.

3. Visualization

Here's how senior data analysts use visualization:

Developed complex algorithms and advanced (undocumented) tableau visualization techniques that were successfully integrated into Tableau dashboard models.
Streamline Tableau Dashboard Visualization, managed dashboards and automated reports for marketing director and other stakeholders.

4. Dashboards

The dashboard is a data management tool used for business intelligence. Dashboards, store, organize and display the scattered data in one system providing easy access to information whenever required. The data is displayed using advanced data visualization techniques, allowing users to understand the intricate patterns in their data. Dashboards make it easier to draw parallels between different data metrics and help in the identification of data trends.

Here's how senior data analysts use dashboards:

Translate business requirements into specification that are used to implement required reports and dashboards, created from potentially multiple data source.
Accomplished at designing dashboards and data summaries for technical and non-technical audiences and facilitating implementation of business strategies and missions.

5. SAS

SAS stands for Statistical Analysis System which is a Statistical Software designed by SAS institute. This software enables users to perform advanced analytics and queries related to data analytics and predictive analysis. It can retrieve data from different sources and perform statistical analysis on it.

Here's how senior data analysts use sas:

Developed fully automated SAS based infrastructure to support campaign execution for new digital marketing channels.
Developed advanced SAS macros to improve program efficiency and provided standardization within and across projects.

6. BI

Here's how senior data analysts use bi:

Worked in BI team to fulfill the needs of regulatory/management/finance/loss mitigation/fraud reporting and 10Q.
Support BI team Tableau reporting operations/ Tableau Administrator.

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7. Statistical Analysis

Here's how senior data analysts use statistical analysis:

Presented statistical analysis methods and results to a wide variety of audiences and converted results into information for decision making.
Develop daily executive management level reports of statistical analysis on business to consumer and business to business marketing campaigns.

8. 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 senior data analysts use hadoop:

Involved in Developing ETL XFR data transformations for distribution data mappings and created HADOOP HDFS files as output.
Analyze scope for implementing Hadoop Distributed platform over legacy data.

9. ETL

Here's how senior data analysts use etl:

Author data mapping and transformation requirements based on understanding of operating rules; review with ETL developers to ensure understanding.
Documented and managed Metadata associated with the ETL processes used to populate Data Warehouse.

10. PowerPoint

Here's how senior data analysts use powerpoint:

Developed allocation models using Oracle Hyperion Financial Management and SAP using Excel and PowerPoint.
Produced monthly PowerPoint commodities trend reports to upper-management up through C-level.

11. SQL Server

Here's how senior data analysts use sql server:

Developed logical and physical data flow models in MS Access/SQL Server for automated data verification and consolidation.
Scheduled package execution using SQL Server Management Studio to execute packages on a daily/weekly basis.

12. 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 senior data analysts use java:

Validated transformed XML files that feed into the global JAVA program when a source record change or enhancement occurs.
Developed POJO classes for database records and used Hibernate as ORM tool to map database records with Java objects.

13. 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 senior data analysts use data warehouse:

Designed Metadata Repository to store data definitions for entities, attributes & mappings between data warehouse and source system data elements.
Ensured operational effectiveness of data warehouse accepting orders from a multitude of fulfillment systems and utilized for company-wide billing and reporting.

14. Excellent Interpersonal

Here's how senior data analysts use excellent interpersonal:

Job skills include excellent interpersonal and oral and written communication skills.

15. 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 senior data analysts use data governance:

Applied Data Governance rules and gathered requirements and prepared different types of documents depending on internal and external stakeholder requirements.
Provided guidance and solution concepts for multiple projects focused on data governance and master data management.

5 Senior Data Analyst- resume examples

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What skills help Senior Data Analysts find jobs?

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

What skills stand out on senior data analyst- resumes?

David Feldman Ph.D.

Professor of Urban Planning and Public Policy and Political Science, Director, Water UCI, Director, MPP Program, University of California, Irvine

Succinct writing, critical thinking, strong quantitative analytical skills.

What senior data analyst- 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 senior data analyst-s need?

Zhixin Wu Ph.D.

Associate Professor, DePauw University

Problem solving skills, analytical skills, self-learning ability, and good communication skills.

What hard/technical skills are most important for senior data analyst-s?

Jason Caudill Ph.D.

Professor of Business, King University

The number one technical skill for today's professionals is the ability to learn new systems. Regardless of expertise in a particular platform, there are going to be updates and changes, and different companies will likely be on different major platforms to perform the same functions. A strong foundation of technical skills in communications software, spreadsheets, and cloud applications will give someone the foundation they need to function in most modern workplaces, but the real skill is being able to translate that understanding of the architecture to multiple platforms so they can manage change.

Do you want to know more?

List of senior data analyst- skills to add to your resume

The most important skills for a senior data analyst- resume and required skills for a senior data analyst- to have include:

Data Analysis
Power Bi
Visualization
Dashboards
SAS
BI
Statistical Analysis
Hadoop
ETL
PowerPoint
SQL Server
Java
Data Warehouse
Excellent Interpersonal
Data Governance
Strong Analytical
Math

Digital Marketing
Patients
Excellent Organizational
VBA
Data Integrity
Metadata
Data Lake
Extraction
Profiling
B Testing
Pivot Tables
Business Processes
Econometrics
Data Warehousing
Data Extraction
Regression
QA

SharePoint
Informatica
Ssis
Client Facing
Database Objects
Oracle Sql
Business Rules
Data Validation
SSRS
Visio
Data Elements
Azure
Physical Data Models
Technical Specifications
Unix
Cognos

Updated January 8, 2025

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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