Senior Data Engineer

DraftKings Inc.•Boston, MA

49d•$116,800 - $146,000

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 Senior Data Engineer, you'll build the data capabilities that power regulatory reporting, financial operations, and intelligent experiences across our platform. You'll create scalable data infrastructure that transforms complex transactional data into trusted, reporting-ready datasets while helping shape the future of our modern data platform. Working across Engineering, Compliance, Analytics, and business teams, you'll solve complex technical challenges, improve how data flows across the organization, and build the foundation that enables AI-powered experiences and smarter decision-making.

Requirements

A Bachelor's Degree in Computer Science or a related field, or an equivalent combination of education, training, and professional experience, with at least 3 years of experience designing, building, and maintaining scalable data platforms and distributed data systems.
Strong proficiency in Python and SQL, with hands-on experience developing both real-time and batch data processing solutions.
Experience building modern cloud-based data platforms using technologies such as Snowflake, Databricks, Kafka, or similar distributed data processing and streaming technologies.
Experience working with cloud infrastructure, preferably Amazon Web Services (AWS), along with infrastructure and DevOps tools such as Terraform, PagerDuty, and Datadog.
Deep understanding of modern data architecture, including data warehousing, data lakes, ETL frameworks, and scalable data modeling techniques.
Experience building trusted data solutions that support financial operations, regulatory reporting, auditability, reconciliation, or other highly governed data domains.
Hands-on experience using AI-assisted engineering tools such as Claude Code, Codex, or similar technologies to automate workflows, build intelligent agents, and accelerate software development.
Strong communication, collaboration, and mentoring skills, with the ability to thrive in a fast-paced environment while partnering effectively across technical and business teams.

Nice To Haves

Experience supporting CFTC-regulated markets or financial services is preferred.

Responsibilities

Build scalable, high-performance data infrastructure that transforms complex transactional and financial data into trusted, reporting-ready datasets supporting regulatory reporting, financial operations, and business insights.
Develop reliable data solutions that prioritize accuracy, completeness, traceability, and auditability while supporting regulatory compliance and highly governed business processes.
Leverage AI throughout the software development lifecycle to improve engineering productivity, enhance data quality, and build trusted data products that enable AI-powered applications and natural language access to data.
Partner with Engineering, Compliance, Analytics, and cross-functional stakeholders to translate complex business and regulatory requirements into scalable, analytics-ready data models and solutions.
Design, optimize, and maintain modern data models while championing best practices for data quality, governance, observability, and platform reliability.
Build and optimize modern cloud-based data pipelines and streaming solutions using technologies such as Snowflake, Databricks, Kafka, or similar distributed data platforms.
Drive engineering best practices for data transformation, streaming, platform performance, and operational excellence while mentoring teammates and contributing to the continued growth of the Data Engineering Team.
Collaborate in an agile environment to deliver scalable, resilient solutions that evolve alongside business priorities and platform capabilities.