Data Engineer, AI Enablement

What you'll do

• Design, build, and operate scalable data pipelines to create curated, reusable data products for R&D.
• Integrate and normalize data from databases, APIs, and external sources into the ARCH data environment.
• Prepare data for AI and knowledge graph use cases by cleaning, labeling, and supporting embedding workflows.
• Establish data foundations that ensure assets are structured, documented, governed, and traceable for downstream consumption.
• Apply data quality and governance practices including metadata management, lineage, and access controls.
• Translate scientific and business requirements into technical specifications for data scientists and machine learning engineers.
• Provide technical guidance to contracted engineers by reviewing outputs and ensuring they meet quality standards.
• Monitor pipeline performance and troubleshoot failures to ensure data freshness and operational reliability.

What we're looking for

• Bachelor’s Degree with 5 years of experience or a Master’s Degree with 4 years of experience in IT, data engineering, data management, analytics, life sciences, or a related field.
• Hands-on experience designing, developing, and operating production data pipelines and curated data products using SQL, Python, ETL/ELT patterns, and workflow orchestration tools like Airflow.
• Working knowledge of modern data platforms, data integration, data warehousing or lakehouse patterns, distributed SQL or big data environments, cloud infrastructure, and analytics enablement.
• Experience preparing data for downstream analytics, machine learning, knowledge graph, or retrieval use cases, including cleaning, standardization, enrichment, and support for embedding or vector-search workflows.
• Experience applying data quality, metadata management, governance, lineage, documentation, and data modeling practices to support trusted, reusable data products.
• Experience collaborating with cross-functional teams to translate requirements and providing technical guidance to contracted, vendor, or managed-services engineers.
• Ability to operate with high autonomy, manage concurrent workstreams, and communicate technical concepts clearly to scientific, technical, and business audiences.
• Pharmaceutical or healthcare industry experience; familiarity with graph databases, AWS, Databricks, Spark, Snowflake, Neo4j, and Agile practices (preferred).