• Design, develop, and maintain ETL workflows to ingest, transform, and deliver data across multiple systems. Ensure pipelines are scalable, reliable, and efficient. • Design schemas, dbt models, and database structures optimized for dashboards and analysis. • Maintain a thorough, meticulously documented, and tested codebase that can be scaled across large datasets. • Collaborate with team members and stakeholders to understand data needs and deliver solutions.

• Develop and maintain data pipelines that process healthcare claims, enrollment, and related administrative data • Own components of data pipelines end-to-end, from raw data processing through final analytic outputs • Translate technical specifications and business rules into well-structured, maintainable code • Work with large-scale healthcare datasets (tens to hundreds of millions of rows) within the VRDC's secure computing environment • Perform data validation, quality checks, and reconciliation to ensure analytic accuracy • Identify opportunities to improve code quality, reduce duplication, and strengthen testing, validation, and documentation • Ensure reproducibility and traceability of results across data refreshes and measurement years • Communicate technical findings, methodology, and data issues clearly to actuarial and consulting staff • Manage concurrent workstreams across multiple measurement years and data refresh cycles

• Develop, implement, and evolve transactional and analytical data structures. • Build data pipelines, integrations, and transformation processes between different systems and information sources. • Support the migration of solutions currently based on SharePoint to a modern, robust, and scalable architecture. • Develop, optimize, and maintain SQL queries, stored procedures, and database schemas. • Prepare and structure analytical layers for consumption in Power BI dashboards and reports. • Ensure data quality, integrity, performance, governance, and reliability. • Work in partnership with solution architects, analysts, and business stakeholders to implement solutions aligned with company needs. • Contribute to the adoption of best practices for version control, deployment automation, and governance of data assets.

Role Description As a Data Engineer II, you will be a key contributor to Reach's data platform modernization efforts. Working closely with Data Engineering, Analytics, Product, and Platform Engineering teams, you will design, build, and maintain reliable data pipelines, transformations, and models that power reporting, analytics, and operational decision-making. This role is ideal for an engineer who can independently deliver solutions to well-defined problems, participate in technical design discussions, and continuously improve the quality and reliability of our data ecosystem. What You'll Do - Design, build, and maintain scalable data pipelines, transformations, and data models using modern ELT practices - Participate in incident response and operational support activities, including occasional off-hours coverage for critical production issues, data incidents, and major platform deployments - Develop and support data assets that enable reporting, analytics, and operational workflows - Participate in technical design discussions and contribute to implementation planning and solution documentation - Collaborate with analysts, data scientists, software engineers, and business stakeholders to understand requirements and deliver effective data solutions - Troubleshoot data quality, reliability, and performance issues across data pipelines and systems - Monitor and improve existing implementations by identifying gaps, inefficiencies, and opportunities for automation - Contribute to engineering best practices around testing, version control, documentation, and data quality - Support deployment and maintenance of data pipelines through established CI/CD processes - Participate in code reviews and provide constructive feedback to peers - Continuously develop technical expertise and apply new tools, techniques, and approaches where appropriate Qualifications - 3–5 years of hands-on experience in Data Engineering, Analytics Engineering, or a related data-focused role - Experience working in a product-oriented data squad, partnering closely with Product, Analytics, and Engineering to deliver end-to-end data solutions and data products - Experience working with modern data platforms and tools such as dbt (Core or Cloud), Amazon RDS, PostgreSQL, or similar technologies; strongly preferred: experience with Snowflake (our primary data warehouse platform) - Strong SQL skills with experience developing data transformations and data models - Experience building and maintaining ETL/ELT pipelines - Experience with Python or a similar programming language - Understanding of data modeling, warehousing concepts, and relational databases - Experience using Git-based development workflows - Ability to independently manage assigned workstreams and deliver high-quality solutions - Strong communication, collaboration, and problem-solving skills - Demonstrated ability to learn new technologies, tools, and business domains and apply them effectively Nice to Have - Experience preparing and modeling data for analysis in Tableau, Sigma, or other BI tools - Experience with reverse ETL / data activation tools such as FiveTran activations, Hightouch, etc. - Familiarity with dbt coding conventions and Medallion data architecture (i.e. Bronze, Silver, Gold data layers) - Experience working in the Financial Services industry and familiarity with working in a SOC2 and PCI-DSS environment Success in This Role - Independently deliver reliable solutions to defined business and technical problems - Balance implementation speed with maintainability and long-term platform health - Create well-structured solutions to known problems and navigate moderate ambiguity - Identify risks within their work and proactively propose mitigations - Effectively troubleshoot user and system issues while contributing to continuous improvement - Expand their technical expertise and apply new learnings to improve outcomes - Collaborate effectively with stakeholders and engineering partners to clarify requirements and deliver value - Contribute positively to team culture through knowledge sharing, collaboration, and constructive feedback Benefits - Remote First Culture with optional Hybrid opportunities - Healthcare, Life Insurance, 401k Match - Paid Time Off, Paid 12-week Parental Leave - Disability (short-term, long-term), Employee Assistance Program - Spending Accounts (Transit/Parking, Medical, Dependent Care) - Insurance Discounts (home, auto, pet) Location - Continental US and Canada - Willing to attend online meetings with staff that are mainly in Eastern and Central time zones - Able to travel to NYC periodically (e.g., 1-2 times a year)