Data Engineer

2 Months ago • 3-5 Years • Data Analyst

Job Summary

Job Description

This part-time Data Engineer role at Electronic Arts focuses on designing, developing, and maintaining ETL pipelines for digital merchandising analytics and reporting. Responsibilities include optimizing data workflows, ensuring data quality, maintaining dashboards in Looker (preferred), Power BI, or Tableau, and collaborating with IT and Data Governance teams. The ideal candidate possesses expertise in ETL processes, data governance, data visualization, SQL, cloud-based ETL tools (e.g., Apache Airflow, AWS Glue), and data modeling. This position requires strong problem-solving and communication skills and experience with large-scale structured and unstructured data. The role also involves supporting A/B testing data pipelines and ensuring data compliance and scalability. Availability on Tuesdays, Wednesdays, and Thursdays is mandatory.
Must have:
  • ETL pipeline design & maintenance
  • Data transformation & database mgmt
  • SQL proficiency & cloud platform exp
  • Data visualization & dashboarding
  • Data governance & compliance
Good to have:
  • Experience with marketing data
  • Python/R for data processing
  • Web analytics tools integration
  • Machine learning for merchandising
  • API experience for data pulling
Perks:
  • Paid time off
  • Parental leave
  • Free games

Job Details

We are looking for a Data Engineer to design, develop, and maintain ETL pipelines and data transformations that support digital merchandising analytics and reporting. This role will be responsible for optimising data workflows, ensuring data quality, and maintaining dashboards for digital merchandising insights. The ideal candidate will have expertise in ETL processes, data governance, and visualisation tools such as Looker (favourable), Power BI, or Tableau. If you are someone who is passionate about structuring data for better accuracy, transforming raw data into elegant data driven visualizations, and has a vision for what an excellent data culture should be then you are in the right place.
*Please note this is a part time role requiring availability on Tuesday, Wednesday and Thursday only.

Responsibilities:

Data Engineering & ETL

  • Design, develop, and maintain ETL pipelines to extract, transform, and load data from various digital merchandising sources (1P analytics platforms, web analytics, internal data systems, etc.).

  • Optimise data integration processes for large-scale structured and unstructured data using data management tools.

  • Ensure data accuracy, consistency, and timeliness across merchandising analytics platforms.

  • Work with SQL and cloud-based ETL tools (e.g., Apache Airflow, AWS Glue, Azure Data Factory, DBT).

  • Automate data ingestion and transformation workflows to support merchandising analytics and decision-making.

  • Collaborate with IT and Data Governance teams to ensure data compliance and quality

Data Governance

  • Develop and optimise data governance, processes and tools to improve digital merchandising teams’ query performance and analytical capabilities.

  • Implement best practices for data normalisation, indexing, and partitioning for performance efficiency.

  • Support A/B testing data pipelines for digital merchandising experimentation with a focus on data privacy and management.

  • Ensure scalability of data transformation workflows as digital merchandising data grows.

Data Visualisation & Dashboard Maintenance

  • Maintain and enhance existing dashboards in Looker (favourable) Power BI or Tableau to support digital merchandising KPIs (e.g., product performance, conversion rates, inventory analytics).

  • Collaborate with merchandising analysts and stakeholders to translate business requirements into insightful visualisations.

  • Implement data visualisation best practices to ensure usability and clarity.

  • Troubleshoot and optimise dashboards for performance and accuracy.

Required Qualifications:

  • Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field.

  • 3+ years of experience in ETL development, data transformation, and database management.

  • Strong proficiency with analytics programming languages (Python, R, etc.) and SQL (writing complex queries, indexing, optimisation).

  • Experience with ETL tools (e.g., Apache Airflow, DBT, AWS Glue, Fivetran, Informatica).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and data storage solutions (Redshift, Snowflake).

  • Experience in data modeling, ETL processes, and data warehousing

  • Knowledge of data visualisation tools (Power BI, Tableau, Looker) and dashboard performance tuning.

  • Understanding of data governance, data security, and compliance standards.

  • Strong problem-solving and analytical skills.

  • Excellent communication skills to collaborate with cross-functional teams.

Preferred Qualifications:

  • Experience working with marketing or digital merchandising data.

  • Familiarity with Python or R for data processing and automation.

  • Knowledge of web analytics tools (Google Analytics, Adobe Analytics) and their integration with ETL pipelines.

  • Hands-on experience with machine learning models for merchandising analytics (optional but a plus).

  • Experience with APIs for pulling digital merchandising and inventory data.

About Electronic Arts

We’re proud to have an extensive portfolio of games and experiences, locations around the world, and opportunities across EA. We value adaptability, resilience, creativity, and curiosity. From leadership that brings out your potential, to creating space for learning and experimenting, we empower you to do great work and pursue opportunities for growth.

We take a holistic approach with our benefits program, focusing on physical, emotional, financial, career, and community wellness to support a balanced life with paid time off and new parent leave, plus free games and so much more. We nurture environments where our teams can always bring their best to what they do.

Electronic Arts is an equal opportunity employer. All employment decisions are made without regard to race, color, national origin, ancestry, sex, gender, gender identity or expression, sexual orientation, age, genetic information, religion, disability, medical condition, pregnancy, marital status, family status, veteran status, or any other characteristic protected by law. We will also consider employment qualified applicants with criminal records in accordance with applicable law. EA also makes workplace accommodations for qualified individuals with disabilities as required by applicable law.

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