Data Scientist
Core
Design, build, and optimize scalable data pipelines and ETL workflows to support user 360 views, churn prediction, and recommendation engine inputs for the video game industry.
Role type
Senior Data Scientist (Data Engineering & ML Ops)
Builds
Production data pipelines, scalable data models, and ML feature pipelines in Snowflake and GCP.
Domain
Video game industry, e-commerce, data engineering, machine learning
Deliverable
production ML models | product features | infrastructure
Required skills
SQL, Python, Spark, Snowflake (Snowpark/Streams/Tasks), Kafka, GCP, data modeling (Kimball/Data Vault), CI/CD, dbt, Airflow/Prefect
Preferred skills
Leading ML teams, deploying ML feature pipelines, ad-tech/gaming/e-commerce domain expertise, feature stores (Feast/Tecton), managing data engineering teams
Technologies
Snowflake, Snowpark, Kafka, GCP, AWS, dbt, Airflow, Prefect, Looker, Tableau, Snowsight, MySQL, BigQuery, Redis
Responsibilities
Design and optimize data pipelines and ETL workflows; Develop scalable data models for churn prediction and recommendations; Mentor junior data engineers on modeling and performance tuning; Partner with ML teams to productionize features; Establish data quality checks and governance standards; Build dashboards for pipeline health and latency metrics.
Seniority
Senior, hands-on IC with leadership responsibilities
