Data Architect - RWD and Analytics Products

Job description We are seeking a Data Architect - RWD and Analytics Products to lead the design and implementation of scalable real-world data (RWD) solutions architecture. This role sits within the Product team but maintains strong collaboration with Engineering to ensure technical feasibility and execution. The ideal candidate has expertise in healthcare data, claims, EHR, lab and other types of RWD and is skilled in translating business needs into scalable, high-impact data products. This role will be instrumental in shaping data-driven products, optimizing data architectures, and ensuring the integration of real-world data assets into enterprise solutions that support life sciences, healthcare, and payer analytics. Responsibilities Define and drive the requirements for RWD data products. Collaborate with leadership, product managers, customers, and data scientists to identify high-value use cases. Translate business and regulatory requirements into scalable and performant data models and solutions. Develop architectures to support payer claims, labs, ehr-sourced insight generation and analytics. Partner with healthcare providers, payers, and life sciences companies to enhance data interoperability. Work closely with Engineering to design and implement responsive analytics layer and data architectures. Provide technical guidance on ETL pipelines, data normalization, and integration with third-party RWD sources. Architect solutions to aggregate, standardize, and analyze EHR and molecular data, ensuring compliance with healthcare regulations (HIPAA, GDPR). Define best practices for claims data ingestion, quality control, and data transformations. Develop frameworks for processing structured and unstructured EHR data, leveraging NLP and data harmonization techniques. Ensure compliance with HIPAA, GDPR, and regulatory frameworks for healthcare data products. Define and implement data governance strategies to maintain high data integrity and lineage tracking. Requirements Deep understanding of payer data, claims lifecycle, EHR, labs and real-world data applications. Ability to translate business needs into technical solutions and drive execution. Strong understanding of data product lifecycle and product management principles. Experience working with cross-functional teams, including Product, Engineering, Clinical, Business and Customer Success. Excellent communication skills to engage with both technical and non-technical stakeholders. Expertise in RWD and payer data structures (claims, EMR/EHR, registry data, prescription data, etc.). Proficiency in SQL and NoSQL databases (PostgreSQL, Snowflake, MongoDB, etc.). Strong knowledge of ETL processes and data pipeline orchestration. Experience with big data processing (Spark, Databricks, Hadoop). Understanding of payer and provider data models used in healthcare analytics. Strong presentation and documentation skills to articulate solutions effectively. Experience working with payer organizations, PBMs, life sciences, and health plans. Experience with OMOP, FHIR, HL7, and other healthcare data standards. Knowledge of data governance, metadata management, and lineage tracking tools. Experience in pharmaceutical RWE studies and market access analytics. Familiarity with BI tools (Tableau, Power BI, Looker). Understanding of data mesh and federated data architectures.