Senior Data Engineer

🕒 vor 11 Tagen

🗣️🇺🇸🇬🇧 Englisch erforderlich

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BetMGM

501 - 1000 Mitarbeiter

Gegründet 2018

🎲 Glücksspiel

🎮 Gaming

👥 B2C

💰 €25.100 Seed Round im 2022-10

Gambling • Gaming • B2C

BetMGM ist der exklusive Sportwetten-Partner von MGM Resorts in ganz Amerika und bietet sowohl Online- als auch physische Casino-Spielerlebnisse an. Als führendes Unternehmen im Bereich Online-Casino und Poker arbeitet BetMGM auch mit Schwester-Marken wie Borgata Online und PartyCasino zusammen. Das Unternehmen setzt sich für die Förderung eines inklusiven Arbeitsumfelds ein und legt großen Wert auf verantwortungsbewusstes Spielen, um eine nachhaltige und angenehme Spielumgebung für seine Kunden zu gewährleisten.

Beschreibung

• Own the path from raw transactional and event data to trustworthy, well-modeled datasets powering BetMGM's analytics, ML, and operational systems. • 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. • 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. • 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. • Own freshness SLAs and data contracts for the gold layer; configure Monte Carlo coverage for volume, freshness, schema, and distribution; triage incidents end-to-end. • Collaborate with analytics engineers, data scientists, and ML platform engineers on shared standards (naming, testing, observability, lineage, cost attribution).

🎯 Anforderungen

• BS or MS in Computer Science, Statistics, Math, or other STEM field — or equivalent practical experience. • 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.

🏖️ Vorteile

• Medical, Dental, Vision, Life, and Disability Insurance • 401(k) with company match • Pre-tax spending accounts including health care FSA and commuter savings • Flexible paid time off • Professional development reimbursement and ongoing skills training opportunities • Employee resource groups • Swag, ticket giveaways, and more!

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