Defining what it means to build and deliver the most extraordinary sports & entertainment experiences.The Crown is Yours
Data Engineer
Location
Massachusetts
Posted
2 days ago
Salary
$101.6K - $127K / year
Seniority
Senior
Job Description
Data Engineer
DraftKings Inc.
• Design, build, and maintain scalable data ingestion pipelines supporting a wide range of source systems (APIs, databases, streaming platforms, third-party data providers) • Develop batch and real-time ingestion frameworks capable of handling high data volumes and low-latency requirements • Build fault-tolerant and resilient pipelines with strong guarantees around data integrity, idempotency, and recovery • Establish and enhance observability, monitoring, and alerting for ingestion pipelines (latency, throughput, failures, data freshness) • Implement and enforce data quality checks and validation frameworks at ingestion points • Contribute to the development of Data Ingestion as a platform product, including reusable frameworks, standards, and best practices • Leverage AI-assisted development tools and automation to accelerate pipeline development, improve code quality, and enhance operational efficiency (e.g., code generation, testing, anomaly detection, workflow automation) • Partner with upstream system owners and downstream consumers to define data contracts, SLAs, and schema evolution strategies • Optimize pipelines for performance, cost, and efficiency across compute and storage layers • Use Infrastructure as Code (IaC) to provision and manage ingestion infrastructure in a consistent and scalable manner • Collaborate with platform, analytics, and data science teams to ensure seamless data availability and usability.
Job Requirements
- 3+ years of experience in data engineering
- Proven experience building high-volume data pipelines (batch and/or streaming) in cloud environments
- Strong hands-on experience with: AWS services (e.g., S3, Lambda, Glue, Kinesis, DMS, EventBridge)
- Python and SQL for data processing and pipeline development
- Orchestration tools (e.g., Airflow)
- Experience working with data lakes and data warehouses (e.g., Snowflake, Redshift, Databricks)
- Experience with streaming and event-driven architectures (e.g., Kafka, Kinesis, CDC pipelines)
- Familiarity with Infrastructure as Code (e.g., Terraform)
- Strong understanding of: Data modeling basics, Schema evolution and data contracts, Fault tolerance and idempotent processing
- Experience implementing monitoring and observability using tools such as Datadog, CloudWatch, or similar.
Benefits
- bonus
- equity
- benefits as applicable
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