Data Engineer – Platform
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Job Description
Data Engineer, Platform at DraftKings building and scaling data ingestion pipelines. Enhance customer experiences and streamline operations through innovative data solutions.
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.
- Experience with data reporting tools (e.g., Tableau), and data logging/monitoring tools is preferred.
- Strong communication and collaboration skills, with the ability to thrive in fast-paced, cross-functional teams.
Benefits:
- Health insurance
- Retirement plans
- Paid time off
- Flexible work arrangements
- Professional development
- Bonuses
- Stock options
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