Hiring: Scientific Technical Engineer - PDS&T CMC Company: BioSpace Location: North Chicago, IL Job Posted Time: 2026-09-17 04:54:56 Target Skills & Keywords : AWS, Accessibility, Airflow, Apache, Azure, CI/CD, Data Mesh, Data Pipeline, Databricks, ELT, ETL, Embedded Systems, Feature Store, GCP, GraphQL, Informatica, LLM, Manufacturing Execution Systems, Microservices, Python, RAG, REST, SQL, Snowflake, Spark, Talend, dbt About the job Experience: •3+ years of hands-on experience designing and building enterprise-grade data pipelines, integration workflows, and data products in complex, multi-source environments. Required Skills: •Principal Data Engineer is a highly technical, AI-native role responsible for designing, building, and operating production-grade data pipelines and data products that power AI/ML, analytics, and automation across AbbVie's CMC and manufacturing ecosystem. •Enterprise-scale scope: Enterprise-scale biologics portfolio spanning clinical, commercial, and lifecycle stages •Building AI playbook for the future: First-in-AbbVie and first-in-biologics analytical approaches; you build the AI playbook for the future •Growth and Impact: Direct impact on regulatory submissions, commercial readiness, and manufacturing decisions through deep cross-functional exposure to manufacturing, quality, regulatory, and scientific leadership •Mission: Every model you build helps ensure safe, reliable medicines reach patients at scale •Design and implement scalable, robust data ingestion pipelines that connect CMC and manufacturing source systems including MES (Manufacturing Execution Systems), process historians, LIMS, QMS, ERP platforms, and instrument data sources to centralized and federated data environments. •Build connectors, adapters, and integration layers that handle the heterogeneous data formats, protocols, and latency profiles characteristic of pharmaceutical manufacturing environments. •Support both batch and real-time/streaming data patterns, selecting appropriate architectures based on use case requirements. Qualifications: •Bachelors Degree Computer Science, Data Engineering, Information Systems, Software Engineering, Bioinformatics, or a closely related technical field plus6 years experience; Masters Degree plus5 years experience; PhD plus0 years experience. •Respective years of hands-on experience designing and building enterprise-grade data pipelines, integration workflows, and data products in complex, multi-source environments. •Expert-level proficiency in Python for data engineering tasks pipeline development, transformation logic, data validation, and automation. •Strong SQL skills across modern analytical and transactional databases; comfort with both ANSI SQL and platform-specific dialects. •Demonstrated experience with cloud data platforms (AWS, Azure, or GCP) and modern data stack components including tools such as dbt, Spark, Airflow, Databricks, Snowflake, or equivalents. •Develop ETL/ELT pipelines using tools such as Informatica, Talend, Apache NiFi, and cloud-native services (e.g., AWS Glue, Azure Data Factory). •Implement master data management (MDM), metadata management, and data cataloging solutions to ensure proper data lineage, accessibility, and compliance. •Set and enforce standards for API development and data integration (REST, GraphQL, OData), enabling seamless integration using microservices architectures. •Ownership orientation: you define your own problem space, drive solutions to completion, and hold yourself accountable to outcomes not just outputs. •Solution-architect instinct: you think before you build, consider the full landscape of available approaches, and choose tools based on fit-for-purpose reasoning rather than familiarity or trend. Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!