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 help will lead the design and implementation of reliable, scalable systems for transforming raw data into structured, usable formats that power data products, reporting, and operational workflows. You'll operate across varied business domains and play a critical role in aligning technical solutions with business strategy. Your work will enable clean, performant data solutions that drive impact at scale. If you're excited about solving complex data challenges in a fast-paced, high-growth environment, come join us and grow your career at DraftKings. Your work will create the next generation of immersive, data-powered gaming experiences that captivate audiences worldwide. What you'll do as a Senior Data Engineer Dive into the world of DraftKings to understand the systems and data structures that support our products Work with engineering, product, and business teams to design data solutions that meet application and reporting requirements. What you'll bring 4+ years of experience in Data Engineering or a closely related field, with demonstrated expertise in building and maintaining production data systems. Advanced SQL skills and deep experience implementing complex business logic and performance-optimized transformations at scale. Expertise with modern cloud-based data platforms (e.g., Snowflake, BigQuery, Redshift) and experience managing large, distributed data environments. Strong understanding of data architecture and dimensional modeling principles, with a track record of designing enterprise-grade schemas. Proven ability to lead projects through agile software development lifecycles and mentor junior team members. Proficiency with version control systems (e.g., Git) and collaborative engineering practices. Ability to quickly learn industry and DraftKings-specific domain knowledge and leverage it to deliver solutions for critical business needs. Join Our Team We're a publicly traded (NASDAQ: DKNG) technology company headquartered in Boston. As a regulated gaming company, you may be required to obtain a gaming license issued by the appropriate state agency as a condition of employment. Don't worry, we'll guide you through the process if this is relevant to your role. The US base salary range for this full-time position is 116,800.00 USD - 146,000.00 USD, plus bonus, equity, and benefits as applicable. Our ranges are determined by role, level, and location. The compensation information displayed on each job posting reflects the range for new hire pay rates for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific pay range and how that was determined during the hiring process. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Block is one company built from many blocks, all united by the same purpose of economic empowerment. The blocks that form our foundational teams - People, Finance, Counsel, Hardware, Information Security, Platform Infrastructure Engineering, and more - provide support and guidance at the corporate level. They work across business groups and around the globe, spanning time zones and disciplines to develop inclusive People policies, forecast finances, give legal counsel, safeguard systems, nurture new initiatives, and more. Every challenge creates possibilities, and we need different perspectives to see them all. Bring yours to Block. The Role The Compliance Engineering & Technology (CET) team at Block supports the detection and reporting of suspicious financial crimes activity across Cash App, Square, and Afterpay. We work globally with partners in business, engineering, counsel, and product to provide a safe user experience for our customers while minimizing and potentially eliminating bad activity on our platform. You will report to the CET - Data Engineering Manager. As a Data Engineer you will handle everything from data architecture and modeling to data pipeline tooling and dashboarding. You will enable other compliance teams to make impactful business decisions by laying the foundation of our large and unique datasets that span across multiple products. You Will Work with engineering and product teams to design, develop, and manage scalable ETL pipelines to unblock new product launches. Create brand new and optimize existing data models and schemas on top of Block data including but not limited to eventing, customer level, and process level data. Build monitoring to assess the health of the team's infrastructure as well as data quality and lineage. Participate in on-call rotation, monitor daily execution, diagnose and log issues, and fix business critical pipelines to ensure SLAs are met with internal stakeholders Work with non-technical partners and product teams to understand their needs, translate business requirements into applicable data requirements, and come up with automated end-to-end solutions.

• Own delivery end to end from technical specs, phased migrations, deprecation plans and more. • Take architectural plans and turn them into shipped software- sequenced, risk-managed and on schedule. • Design and implement backend services that handle complex business logic- configuration management, workflow orchestration, data validation and integrations across internal and external systems. • Design APIs, model data, write tests and review pull requests that make the whole team better. • Collaborate on architecture, define domain boundaries, set API standards and bring your own ideas about how to solve hard problems. You will have real influence over how these systems evolve. • Pilot tools where they help, document patterns and scale what works. AI assists; engineers remain accountable for correctness, security and privacy. • Define testing strategies, establish observability standards and strengthen runbooks. • Mentor engineers through code reviews, pairing and technical guidance. • Partner with Product, Partnerships and Clinical Operations to understand requirements and partner-facing implications. • Coordinate with Data/AI on integration points.

• Lead the design and evolution of scalable data architectures, supporting batch, streaming, and AI-driven workloads. • Own end-to-end data pipelines —from ingestion and transformation through to serving analytics and ML/GenAI use cases. • Define and enforce data engineering standards across modelling, orchestration, observability, and reliability. • Mentor and guide data engineers through code reviews, design discussions, and architectural decisions. • Translate business problems into scalable technical solutions, balancing speed, quality, and long-term maintainability. • Drive the use of agent-based solutions across the development lifecycle, designing autonomous and semi-autonomous workflows that deliver measurable business value. • Clearly document architectures and workflows to support shared understanding and operational excellence. • Build and optimize data pipelines using Databricks, Spark (PySpark), Snowflake, Apache Airflow, and Terraform. • Design performant data models and lakehouse structures (Delta, Unity Catalog) for analytics and downstream AI consumption. • Leverage AWS-native services (e.g. S3, EMR, DynamoDB) to deliver cost-efficient, production-grade solutions. • Implement robust data quality, testing, and monitoring (e.g. Great Expectations, logging, alerting). • Design data pipelines that power Generative AI applications, including data preparation, enrichment, and feature generation. • Integrate 3rd party APIs into data workflows for use cases such as: Automated data enrichment and classification Intelligent summarization and insight generation Metadata generation and semantic search enablement AI-assisted reporting and decision support. • Collaborate with ML and Product teams on prompt design, evaluation, and governance, ensuring responsible and reliable AI usage.