Data Engineer, Platform

DraftKings Inc.

1d•$101,600 - $127,000

About The Position

At DraftKings, AI is becoming an integral part of both our present and future, powering how work gets done today, guiding smarter decisions, and sparking bold ideas. It’s transforming how we enhance customer experiences, streamline operations, and unlock new possibilities. Our teams are energized by innovation and readily embrace emerging technology. We’re not waiting for the future to arrive. We’re shaping it, one bold step at a time. To those who see AI as a driver of progress, come build the future together. The Crown Is Yours As a Data Engineer, Platform, you will play a critical role in building and scaling the foundational ingestion layer of our data ecosystem. This role focuses on designing and developing high-throughput, fault-tolerant data pipelines that integrates a diverse set of upstream systems into our data lake and data warehouse platforms. You will work on high-volume, high-frequency data ingestion (batch and real-time), ensuring reliability, observability, and data quality across the platform. In addition to hands-on engineering, you will contribute to evolving Data Ingestion as a platform product, driving standardization, performance optimization, and automation - including leveraging AI-assisted development and intelligent automation frameworks.

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.

Nice To Haves

Experience with data reporting tools (e.g., Tableau), and data logging/monitoring tools is preferred

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.