Senior Data Engineer

Job summary

Discover What’s Possible at BetMGM Ready to make your career legendary? Join us as we bring the magic of Vegas to our players. The BetMGM team has over 1,400 talented members, revolutionizing sports betting and online gaming in the United States and Canada.

Benefits

Qualifications

• BS or MS in Computer Science, Statistics, Math, or other STEM field — or equivalent practical experience.
• Practical experience wins ties.
• Must-Haves
• 5+ years building production data pipelines on a modern stack (Python + SQL + dbt + cloud).
• Deep Snowflake — beyond SQL into administration: warehouse sizing, RBAC, resource monitors, Streams/Tasks, Dynamic Tables, secure data sharing, cost tuning via ACCOUNT_USAGE.
• Strong AWS — S3, ECS/Fargate, Lambda, IAM, Secrets Manager, VPC — plus production experience with at least one of EMR Serverless, Glue, or MWAA.
• Terraform for both cloud and Snowflake — you have owned IaC, not just touched it.
• Orchestration fluency — Prefect, Airflow, or Dagster — and an opinion about when each is the right tool.
• CI/CD ownership — you have built quality gates that block bad code, not just YAML pipelines that pass.
• Bias toward outcomes — you describe past work in terms of SLAs, incidents, and customers served, not tool checklists.
• Nice-to-Haves
• Snowflake-native ML (Snowpark, Cortex AISQL, Snowflake Notebooks) for in-warehouse scoring or unstructured workloads.

Responsibilities

• Pipeline & Platform Engineering
• Design, build, and operate batch, micro-batch, and streaming pipelines feeding Snowflake — Prefect-orchestrated flows on ECS Fargate, dbt for transformation, Snowpipe Streaming and Kafka for event ingestion.
• Own the full dbt lifecycle (sources staging intermediate marts) with model contracts, freshness SLAs, automated tests, and version-controlled documentation.
• Stand up Snowflake objects (warehouses, RBAC, resource monitors, Dynamic Tables, Iceberg tables) through Terraform — no ClickOps in production.
• AWS Platform Ownership
• Build AWS-native infrastructure for data workloads — S3, ECS Fargate, Lambda, EMR Serverless, Glue Catalog, IAM, Secrets Manager, VPC endpoints — entirely in Terraform.
• Maintain CI/CD pipelines (GitLab CI or GitHub Actions) that gate every change with linting, dbt build, unit tests, contract checks, and AI-assisted code review.
• Snowflake Depth
• Tune warehouse sizing, clustering, and query patterns for cost and latency; instrument credit usage via ACCOUNT_USAGE; right-size before scaling up.
• Design RBAC, masking policies, and row-access policies that satisfy a regulated operator without becoming an access bottleneck.
• Bring newer Snowflake capabilities to bear — Dynamic Tables, Snowpipe Streaming, Iceberg, Cortex AISQL — when they are the right answer, not because they are new.
• Data Quality & Observability

Skills

Certifications

Degrees

Industry

Company size

Security clearance