Role Description The Data Engineer will support the growth of leading-edge health and human service data projects that use data to transform care across the nation. This role is responsible for working simultaneously on more than one project within a team that includes technical experts, data engineers, data scientists, research associates, project managers, and subject matter experts – to achieve project goals and deliverables. The Data Engineer is responsible for designing, building, and optimizing scalable data solutions that support organizational analytics, reporting, and data quality initiatives. This role works independently on complex data engineering tasks and owns end-to-end data pipelines, integrations, and performance optimization using SQL, Python, and Microsoft Azure technologies. Qualifications - Bachelor’s degree in computer science, information systems, or related field (or equivalent experience) - 3–5 years of experience in data engineering or related roles - Strong proficiency in SQL and Python - Experience with Azure data services and data pipeline design - Experience building and optimizing data pipelines, architectures, and datasets - Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement - Experience supporting and working with cross-functional teams in a dynamic environment - Excellent attention to detail - Awareness of DevOps and Agile principles - Intermediate to advanced expertise with RESTful APIs, XML, JSON, C#, JavaScript, jQuery, and Azure Data Factory - Promote teamwork and team-building Requirements - Design, develop, and maintain scalable data pipelines and automation workflows - Own and optimize ETL/ELT processes using SQL, Python, and Azure data technologies - Develop and maintain REST APIs and other data integration mechanisms - Integrate new and external data sources into production data environments - Monitor, test, and optimize data systems for performance and reliability - Define and implement data quality checks and reporting frameworks - Design and maintain dashboards, scorecards, and reports - Collaborate with cross-functional teams to improve data systems - Mentor Associate Data Engineers - Attend staff, team, and other required meetings and trainings Benefits - Health - Dental - Short- and long-term disability - Life Insurance - 403(b) retirement plan - Flexible spending accounts - Education assistance program - 10 paid holidays - Remote work stipends (e.g., home office improvements, internet/mobile services) Company Description HSRI is a nonprofit organization that conducts research and evaluation to improve health and human service systems. We work at the local, state, and federal levels. Our goal is to help public agencies understand and demonstrate the real-world impact of the services they provide, helping them transform their policies and practices to address root causes of disparities and improve health outcomes. Our teams have an unwavering commitment to envisioning equitable policies and solutions that create a stronger society for us all. HSRI is an equal opportunity employer and is committed to building a diverse team, bringing as many possible perspectives as possible to bear on services that can profoundly affect people’s health and well-being by addressing social determinants of health. We are committed to building an inclusive environment where people of all backgrounds can come to do their best work.

• Define and execute the data product strategy and roadmap aligned with company objectives, customer needs, and data-driven growth opportunities. • Develop business cases and investment recommendations for new platform capabilities, data services, and strategic enhancements that improve scalability, interoperability, and customer value. • Lead cross-functional teams to deliver scalable data products and insights solutions. • Translate business requirements into data product capabilities, prioritizing initiatives that drive measurable business outcomes. • Partner with engineering and analytics teams to develop, launch, and optimize data platforms, reporting solutions, and advanced analytics products. • Conduct market research, customer discovery, and competitive analysis to identify emerging data opportunities and inform product investments. • Define and monitor KPIs for data products, leveraging analytics to measure performance, user adoption, business impact, and continuous improvement opportunities. • Evaluate new data monetization opportunities, develop business cases, and assess financial impact for data-driven offerings and partnerships. • Collaborate with Sales, Marketing, Customer Success, and Partner teams to understand customer needs and uncover opportunities for data-enabled solutions. • Develop data product positioning, value propositions, and go-to-market strategies to drive adoption and revenue growth. • Partner directly with customers and strategic accounts to gather requirements, validate product-market fit, and identify opportunities for innovation. • Serve as the voice of the customer and business stakeholder, ensuring data products deliver actionable insights, usability, trust, and measurable value. • Lead stakeholder presentations, product demonstrations, and roadmap discussions to drive alignment, adoption, and engagement. • Collaborate with Customer Success, Account Management, and Sales teams to identify expansion opportunities and maximize the value of data products and analytics solutions.

• Design and implement scalable, high-performance data architectures across cloud and hybrid environments • Define and enforce data modeling standards, including conceptual, logical, and physical data models • Build and optimize enterprise data pipelines and data integration frameworks to support analytics and operational use cases • Architect and manage data platforms leveraging technologies such as Snowflake, Databricks, Spark, and Azure Data services • Collaborate with data engineers, data scientists, and business stakeholders to translate business needs into robust data solutions • Establish and maintain data governance, data quality, and metadata management frameworks • Ensure data privacy, security, and compliance requirements are met across all platforms and pipelines • Lead architecture decisions for data storage solutions including data lakes, data warehouses, and real-time data processing systems • Optimize performance and cost efficiency of data platforms and workloads • Support Agile delivery frameworks and contribute to sprint planning, backlog grooming, and architectural roadmaps • Implement and oversee CI/CD pipelines and infrastructure-as-code practices for data solutions • Evaluate emerging technologies and recommend solutions to enhance data capabilities

• Assemble large, complex data sets that meet business requirements through extraction, transformation, and loading of data from a wide variety of data sources. • Provide operational support and troubleshooting for existing processes and systems. • Work closely with architects, solution leads, data owners, Data Scientists and key stakeholders to facilitate and coordinate the data platform backlog grooming process, triaging new feature requests in preparation for future project activities. • Deliver automation & efficient processes to ensure high quality throughput & performance of the entire data & analytics platform. • Ensure data extraction, transformation and loading data meet data security & compliance requirements. • Engage with data source platform leads to gain tactical and strategic understanding of data sources required by Agency Data Services AI/ML as well as Data Office standards. • Create data tools for data scientist team members that assist them in building and optimizing models.