AI Data Engineer 3
Role details
Job location
Tech stack
Job description
- Develop subject matter expertise in business and data domains to collaborate with stakeholders and assist with data access.
- Identify and analyze multi-structured data to select accurate data that fulfills analytics requirements, documenting sources and definitions.
- Design data models, architect dataflows, and build abstractions that scale for analytics and machine learning.
- Architect, build, and maintain automated pipelines using modern data engineering practices to deliver clean, enriched, and reliable data.
- Advance infrastructure by creating frameworks, reusable components, and new capabilities.
- Enable franchise performance marketing through development of relevant and robust data products.
Requirements
We are seeking a Senior Analytics Engineer to join our dynamic Player and Data Analytics team. The ideal candidate will have strong experience in building scalable data pipelines, crafting robust data models, and delivering data products for analytics and marketing and a proven ability to translate complex data into actionable insights that drive business impact.
Top 3 must have skills:
Python 4-5 years
Data Modeling 3 years
Marketing 2 years, * Bachelor's in Computer Science, Software Engineering, Computer Engineering, or related field and 4+ years in analytics engineering, data engineering, data science, data analysis, or related software development; or Master's and 3+ years; or equivalent experience.
- 2+ years as an Analytics Engineer or Data Engineer collaborating with business stakeholders on large enterprise systems.
- Experience building, maintaining, and optimizing enterprise-scale pipelines for logs and event streaming data on cloud platforms using tools such as Spark and Airflow; Azure preferred.
- Proficiency with SQL and advanced Python for data transformation and automation.
Candidate Requirements
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Disqualifiers: Repetitive, overly long, or generic or keyword heavy resumes that lack context on impact or outcomes (ex, just listing tools/tech without explaining business value) will likely be disqualified
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Best vs. Average: The ideal resume would contain resumes that clearly demonstrate how their work drives business impact (ex. improved performance, enabled decision making, supported marketing or product outcomes) and show strong critical thinking and problem solving in how they present their experience.
Preferred Skills:
- Critical thinking and problem solving with a creative and open mindset.
- Proven delivery of analytic solutions and data products with measurable business impact.
- Data analysis and exploration skills to select and prepare data for analytics.
- Business acumen to address challenges through analytics engineering.
- Experience with Spark and Airflow on Azure for log and event streaming pipelines.
- Working knowledge of DevOps and DataOps.
- Video game domain knowledge as a player or industry professional.
Benefits & conditions
- Competitive compensation and benefits.
- Opportunities for growth with global clients.
- A supportive, inclusive culture that values innovation and people.
- Exposure to cutting-edge technologies and projects.
Additional Role Details
- Schedule: Monday to Friday, 40 hours per week, no overtime expected.
- Chance for extension: Yes.
- Equipment: Supplier to provide.
- Assessment process: One round with sponsor (45 minutes); a second round with an FTE if needed.