Data Engineer – Platform

DraftKings Inc.

Data Engineer, Platform at DraftKings building and scaling data ingestion pipelines. Enhance customer experiences and streamline operations through innovative data solutions.

Posted 7/15/2026full-timeRemote • Massachusetts • 🇺🇸 United StatesJunior💰 $101,600 - $127,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining scalable data ingestion pipelines, with proficiency in Python and SQL for real-time data streaming. Familiar with cloud infrastructure, data quality frameworks, and modern data stack tools to ensure efficient data availability and usability.

Highest-signal resume keywords

Data Ingestion Pipeline DevelopmentPython ProgrammingSQL ProficiencySnowflake and Databricks ExperienceInfrastructure as Code (IaC) with Terraform

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringReal-Time Data StreamingData Quality ChecksETL Pipeline DesignData Modeling TechniquesNoSQL DatabasesData WarehousingBatch ProcessingMonitoring and AlertingAutomation Tools

Soft Skills

Strong CommunicationCollaboration Skills

Tools & Technologies

KafkaAmazon Web Services (AWS)TerraformPagerDutyDataDogTableau

Industry Keywords

Data IngestionData LakesData WarehousesCloud InfrastructureDevOps

Tech Stack

Tools & technologies

AWSCloudDynamoDBETLKafkaMongoDBNoSQLPythonSQLTableauTerraform

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

Health insurance
Retirement plans
Paid time off
Flexible work arrangements
Professional development
Bonuses
Stock options