Associate Scientific Technical Engineer II, PDS&T CMC
AbbVie
August 11, 2026
Remote friendly (North Chicago, IL)
United States
$65,500 - $125,500 USD yearly
Operations
Responsibilities:
- Design and implement scalable data ingestion pipelines connecting MES, historians, LIMS, QMS, ERP, and instrument sources to centralized/federated data environments.
- Build connectors/adapters handling heterogeneous formats, protocols, and latency; support batch and real-time/streaming ingestion.
- Develop harmonized data models and ontologies; execute semantic mapping to enterprise standards (fields, units, identifiers).
- Implement automated data quality controls, validation, anomaly detection; maintain lineage/metadata for traceability.
- Establish observability (monitoring/alerting/SLA tracking) and support governance aligned with GxP and 21 CFR Part 11.
- Architect governed, versioned reusable data products for AI/ML (feature stores, curated datasets, vector-ready layers for RAG/LLM).
- Contribute to PDST cloud platform (lakehouse, cataloging, access control, compute); implement IaC, CI/CD, automated testing; provide production operational support.
- Influence technical decisions through scientific rigor and business impact.
Qualifications:
Required:
- BS (CS/Data Eng/IS/SE/Bioinformatics or related) + 2 years OR MS with 0 years.
- Hands-on enterprise data pipelines/integration/data products in multi-source environments.
- Expert Python; strong SQL (ANSI and dialects).
- Cloud data platform + modern stack (dbt, Spark, Airflow, Databricks, Snowflake, etc.).
- ETL/ELT (Informatica/Talend/NiFi; AWS Glue/Azure Data Factory, etc.).
- MDM/metadata/data cataloging for lineage/compliance.
- API/data integration standards (REST/GraphQL/OData) for microservices.
- Data modeling tools (e.g., Erwin/PowerDesigner/dbt). Ownership, solution-architect mindset, scientific integrity, credibility, bias for impact.
Preferred:
- Life sciences regulated manufacturing experience.
- GxP/21 CFR Part 11/data integrity knowledge.
- Familiarity with MES, process historians (OSIsoft PI/AVEVA), LIMS, QMS, ERP.
- AI/ML data infrastructure (feature engineering, training datasets, RAG vector/embedding layers).
Benefits (as stated):
- Paid time off (vacation, holidays, sick), medical/dental/vision insurance, 401(k) (eligible employees); short-term incentive program eligibility.
- Design and implement scalable data ingestion pipelines connecting MES, historians, LIMS, QMS, ERP, and instrument sources to centralized/federated data environments.
- Build connectors/adapters handling heterogeneous formats, protocols, and latency; support batch and real-time/streaming ingestion.
- Develop harmonized data models and ontologies; execute semantic mapping to enterprise standards (fields, units, identifiers).
- Implement automated data quality controls, validation, anomaly detection; maintain lineage/metadata for traceability.
- Establish observability (monitoring/alerting/SLA tracking) and support governance aligned with GxP and 21 CFR Part 11.
- Architect governed, versioned reusable data products for AI/ML (feature stores, curated datasets, vector-ready layers for RAG/LLM).
- Contribute to PDST cloud platform (lakehouse, cataloging, access control, compute); implement IaC, CI/CD, automated testing; provide production operational support.
- Influence technical decisions through scientific rigor and business impact.
Qualifications:
Required:
- BS (CS/Data Eng/IS/SE/Bioinformatics or related) + 2 years OR MS with 0 years.
- Hands-on enterprise data pipelines/integration/data products in multi-source environments.
- Expert Python; strong SQL (ANSI and dialects).
- Cloud data platform + modern stack (dbt, Spark, Airflow, Databricks, Snowflake, etc.).
- ETL/ELT (Informatica/Talend/NiFi; AWS Glue/Azure Data Factory, etc.).
- MDM/metadata/data cataloging for lineage/compliance.
- API/data integration standards (REST/GraphQL/OData) for microservices.
- Data modeling tools (e.g., Erwin/PowerDesigner/dbt). Ownership, solution-architect mindset, scientific integrity, credibility, bias for impact.
Preferred:
- Life sciences regulated manufacturing experience.
- GxP/21 CFR Part 11/data integrity knowledge.
- Familiarity with MES, process historians (OSIsoft PI/AVEVA), LIMS, QMS, ERP.
- AI/ML data infrastructure (feature engineering, training datasets, RAG vector/embedding layers).
Benefits (as stated):
- Paid time off (vacation, holidays, sick), medical/dental/vision insurance, 401(k) (eligible employees); short-term incentive program eligibility.