• Implement data integration architecture and solutions for our Investments and Hedging delivery teams. • Design and develop ETL logic using Informatica Informatica Data Management Cloud, Snowflake and various Azure data tools to support existing and future deployments • Design and execute technical aspects of data management functions including creating, loading, transforming, cleansing, processing, analyzing, and visualizing data • Collaborate directly with teammates and business partners to build technical solutions that solve problems, are reusable, scalable, fast, and maintainable through large datasets, both clean and un-clean • Work with multiple development technologies including SQL • Interact cross-functionally with other technical teams both internally and externally to implement complete technology solutions • Design and develop code to support existing and future deployments • Independently solve problems and fix technical issues • Responsible for unit test construction and execution

• Architect and evolve scalable data ingestion and egress frameworks and pipelines that are well tested and offer strong data quality monitoring. • Architect and evolve our CI/CD processes - enhancing the testing environment and observability (such as building LLM-driven reviews with context awareness through data diffing, lineage analysis / downstream impact analysis, and general context). • Architect delivery architecture of data assets to external team partners to reduce manual operational overhead associated with month end close. • Enhance our Claude Code / LLM development support capabilities - creating tools / skills / agents that give our LLMs more context and help us continually improve their abilities to debug, create code, and maintain systems. • Enhance our security posture in our AWS / Databricks environment. • Design and implement distributed data processing systems using Spark and Databricks on AWS. • Establish clear ingestion and integration boundaries that eliminate single points of failure. • Proactively surface risks, dependencies, and tradeoffs before they impact delivery. • Produce clear technical artifacts and recommendations for stakeholders and leadership. • Design logical and physical data models balancing flexibility, performance, governance, and scalability. • Partner closely with the Analytics Engineers on the Finance Data Team to support high-quality downstream data modeling & reporting. • Harden pipelines with monitoring, alerting, SLAs, and recovery mechanisms. • Mentor engineers and elevate distributed systems rigor across the team.

• Lead the design and implementation of data components • Ensure data synchronization across all necessary systems • Maintain a high level of security to protect sensitive data • Align systems with legal and regulatory requirements

Role Description We are looking for a collaborative Data Engineer II. You have a strong inclination to work in rapidly developing and expanding organizations and possess the necessary background to do so. You are well-acquainted with the fast-paced, high-volume, and uncertain nature of operations in the organization, and perceive it as a chance to deliver significant outcomes. - Design and implement data models in partnership with product, analytics, and engineering teams so they are scalable, well-documented, and aligned to business needs. - Collaborate with other Data Engineers to solve problems that directly impact enterprise customers. - Build data transformations and data flows utilizing Python, SQL, DBT, Postgres, and Snowflake. - Build out automated ETL jobs that reliably process large amounts of data, and ensure these jobs run consistently and are well-monitored. - Build tools that enable other data engineers to work more efficiently. - Tune existing implementations to run more efficiently as they become bottlenecks, or migrate existing implementations to new paradigms as needed. - Learn and apply knowledge about the drug discount space, and become a subject matter expert for internal teams to draw upon. Qualifications - Bachelor’s degree in computer science or similar field, or equivalent experience. - 2-4+ years of work experience as a Data Engineer in a professional full-time role. - Advanced knowledge of SQL and Python (along with data analysis libraries such as Pandas, NumPy, and others). - Strong data modeling experience (understanding of SQL, NoSQL, and other database types along with relational modeling). - Ability to learn new technologies and work in various components across the full tech stack. - Experience with cloud native infrastructure (Azure preferred). - Experience with Container Applications (Docker). - Experience building ETL pipelines and other services. - Experience with GenAI Tools and Workflows. - Professional experience in application programming with an object-oriented language. Requirements - Experience with DBT and Snowflake. - Experience with event driven platforms. - Experience with infrastructure as code tools like Terraform. - Knowledge about the drug discount space and healthcare industry. Benefits - Medical, Dental, and Vision benefits. - 401k with company match. - Flexible PTO with a 10 day minimum. - Mobile & Wifi Reimbursement. - Commuter Reimbursement. - Donation matching for charitable contributions. - Travel reimbursement for healthcare services not available near your home. - New employee home office setup reimbursement. - This role can be remote in the United States or hybrid in Chicago or Boston. - Expected Salary Range: $130,000-$145,000 base + bonus.