Role Summary Lead solution design and delivery execution for data, analytics, and AI initiatives primarily within one or more Life Sciences domains (Clinical, Commercial, or Medical AAairs). Provide architectural leadership, guide engineering teams, and ensure high‑quality, secure, and compliant data solutions for pharma and biotech clients. Key Responsibilities Design end‑to‑end data and analytics platform architectures for Life Sciences use cases. Build scalable solutions on cloud platforms (AWS and/or Azure) using modern data engineering and analytics patterns. Work with Life Sciences datasets across at least one primary domain (Clinical or Commercial or Medical AAairs) and collaborate across domains as needed. Create solution blueprints, architecture diagrams, and phased implementation roadmaps. Lead technical delivery for one or more client engagements, partnering with delivery managers and engineering leads. Conduct design reviews, guide development teams, and ensure solution quality and maintainability. Ensure adherence to data governance, security, and regulatory requirements (e.g., HIPAA, GxP). Support operational activities by improving data reliability, observability, and automation. Contribute reusable assets, reference architecture, and best practices to the data & analytics practice. Identify opportunities where AI/ML or GenAI can enhance analytics, automation, or decision support. Must‑Have Qualifications Bachelor’s degree in computer science/software engineering or equivalent combination of education and experience. 8–12+ years of experience in data engineering, analytics architecture, or technical delivery roles. Demonstrated experience in Life Sciences / Pharma / Biotech domain, with hands on exposure to at least one functional area. Clinical (e.g., EDC, CTMS, IRT, Labs) Commercial (e.g., CRM, 3PL, Claims, Hub, Dispense) Medical AAairs / Real‑World Data Hands‑on experience with leading cloud platforms & services including: S3, Glue, Lambda, Redshift, RDS, EMR, Athena, Step Functions, Azure Data Lake, ADF, Synapse, Functions, Key Vault, Event Hub etc. Experience with modern data platforms such as Snowflake and/or Databricks. Strong working knowledge of SQL, and experience with Python and/or Spark. Good understanding of data lake / Lakehouse architectures and ELT patterns. Experience working in regulated or compliance‑driven environments. Experience integrating pharma datasets & systems. Experience/good understanding reporting platforms, proven experience leading multi‑phase or multi‑team delivery. Excellent communication and client‑facing leadership. Good‑to‑Have Skills Experience with BI and reporting tools (Power BI, Tableau, Spotfire). Familiarity with GenAI or ML concepts (e.g., use‑case identification, RAG patterns, LLM‑based analytics). Experience with Master Data Management (MDM) or data quality frameworks. CI/CD, infrastructure‑as‑code, or automation experience (e.g., Azure DevOps, GitHub Actions, Terraform). Cloud or data platform certifications (AWS, Azure, Snowflake, Databricks). Experience designing APIs or data services for ingestion and consumption. #J-18808-Ljbffr