Data Engineer, Platform

DraftKings Inc. is a technology company that is integrating AI into its operations to enhance customer experiences and streamline processes. As a Data Engineer, Platform, you will design and develop data ingestion pipelines, ensuring reliability and data quality while collaborating with various teams to optimize data availability.

Responsibilities:

• 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
• 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

Requirements:

• At least 1 year of experience in data engineering, with a strong focus on data ingestion and pipeline development
• Proficiency in Python and SQL, with hands-on experience developing real-time data streaming solutions
• Working knowledge of Snowflake, Databricks, and Kafka in a modern data stack
• Familiarity with cloud infrastructure and DevOps tools such as Terraform, PagerDuty, and DataDog
• Experience designing data warehouses, data lakes, and ETL pipelines using modern data modeling techniques
• Exposure to cloud platforms, preferably Amazon Web Services (AWS)
• Experience with NoSQL databases like MongoDB or DynamoDB
• Strong communication and collaboration skills, with the ability to thrive in fast-paced, cross-functional teams
• Experience with data reporting tools (e.g., Tableau), and data logging/monitoring tools is preferred