- 4+ years relevant industry experience in a data engineering role and graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field
- Experience developing business relevant, scalable, cost and compute optimized data pipelines
- Proficiency in writing SQL queries and knowledge of cloud-based databases like Snowflake, Presto, Redshift, BigQuery or other big data solutions for both relational and non-relational data types
- Experience with data modelling and data transformation tools such as dbt
- Proficiency in at least one of the programming languages like Python or Java and understanding of Software Engineering principles such as Object-oriented design
- Experience with one of data pipeline and tasks management automation tools such as Airflow
- Experience with one of leading cloud service provides - AWS, GCP or Azure
- Experience in debugging, root cause analysis, monitoring and data pipelines operations support
- Experience with engineering development ecosystem involving Git, CI/CD pipelines, unit testing, code release and deployment
- Inclination towards building technical documentation and knowledge sharing
- Comfortable working with a multi-functional team, both locally and remote, understanding the perspectives of each partner
- Experience working in an Agile development environment and familiar with process management tools such as JIRA, Target process, Trello or similar
Base City:
Remote-Canada - Remote
Salary:
$96k to $133k
Rating:
Self-taught:
Position Type:
Full-time
Position Keywords:
- Agile
- Airflow
- AWS
- Bachelor - Computer Science
- Big Data
- Big Query
- Business Requirements
- CI/CD
- Data Analytics
- Data Engineering
- data model
- Data Pipelines
- Data Transformation
- DBT
- debugging
- Electronic Arts
- ETL
- Git
- Java
- Jira
- Microsoft Azure
- Object Oriented Design
- Presto
- Python
- Redshift
- Reporting
- Root Cause Analysis
- Snowflake
- SQL
- Target Process
- Trello
- Unit Testing
Required:
Bachelor - Computer Science
Experience:
4 Years Data Engineering
Other Experience:
About the Job:
We are a global team of creators, storytellers, technologists, experience originators, innovators and so much more. We believe amazing games and experiences start with teams as diverse as the players and communities we serve. At Electronic Arts, the only limit is your imagination.
What they want you to do:
We are looking for an experienced Data Engineer with broad technical skills and ability to work with large amounts of data. You will collaborate with the Game teams to implement data strategies and develop complex ETL pipelines that support dashboards for promoting deeper understanding of our games.
You will have experience developing and establishing scalable, efficient, automated processes for large scale data analyses. You will also stay informed of the latest trends and research on all aspects of data engineering and analytics. You will work with leaders from an internal Game Studio, providing them with data for understanding game and player insights and report to the Technical Lead for this group.
Key Responsibilities:
- As a Data Engineer you will be involved in the entire development life cycle, from brainstorming ideas, to analysts checkins, to architecture alignment, to implementing elegant solutions to obtain data insights.
- You will gather requirements, model and design solutions to support reporting analytics, and exploratory analysis.
- You will implement efficient, scalable and reliable data pipelines to move and transform data.
- You will work with analysts, understand requirements, develop technical specifications for ETLs, including documentation.
- You will support production code to produce comprehensive and accurate datasets.
- You will guide communications between our users and studio engineers to provide scalable end-to-end solutions.
- You will promote strategies to improve our data modelling, quality and architecture
- You will work with big data solutions, data modelling, understand the ETL pipelines and dashboard tools.
- Explore data and suggest new opportunities to measure and assess the performance of our marketing and commercial actions.