Associate Scientific Technical Engineer II, PDS&T CMC
AbbVie
August 17, 2026
Remote friendly (Worcester, MA)
United States
$65,500 - $125,500 USD yearly
Operations
Responsibilities:
- Design and implement scalable data ingestion pipelines connecting CMC/manufacturing systems (MES, historians, LIMS, QMS, ERP, instruments) to centralized/federated data environments.
- Build connectors/adapters/integration layers for heterogeneous data formats, protocols, and latency; support batch and real-time/streaming patterns.
- Develop and maintain harmonized data models/ontologies; execute semantic mapping of fields, units, and identifiers to enterprise standards.
- Implement automated data quality controls, validation, anomaly detection; build lineage/metadata for traceability; establish monitoring/alerting/SLA practices.
- Support data 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/LLMs).
- Partner with data scientists/ML engineers/process modelers to translate model needs into scalable infrastructure.
- Contribute to PDST cloud platform evolution (lakehouse, cataloging, access control, compute); use IaC, CI/CD, automated testing; onboard new data domains/sites; provide operational support.
- Influence technical decisions through scientific rigor and demonstrated business impact.
Qualifications (Required):
- BS (or related) + 2 years, or MS + 0 years.
- Enterprise-grade experience designing/building pipelines, integration workflows, and data products.
- Expert Python; strong SQL (ANSI + dialects).
- Cloud data platforms (AWS/Azure/GCP) and tools (dbt, Spark, Airflow, Databricks, Snowflake or equivalents).
- ETL/ELT (Informatica, Talend, NiFi, AWS Glue, Azure Data Factory).
- MDM/metadata management/data cataloging for lineage and compliance.
- API/integration standards (REST/GraphQL/OData) with microservices.
- Data modeling (Erwin/PowerDesigner/dbt).
- Ownership, fit-for-purpose solution design, scientific integrity, credibility/influence, bias for impact.
Qualifications (Preferred):
- Pharma/biotech regulated life sciences manufacturing experience.
- GxP/21 CFR Part 11/data integrity familiarity.
- MES/historians (OSIsoft PI/AVEVA), LIMS, QMS, ERP exposure.
- AI/ML data infrastructure experience (feature engineering, training datasets, RAG embeddings/vector layers).
Benefits (explicitly stated):
- Paid time off (vacation, holidays, sick), medical/dental/vision insurance, 401(k); eligibility for short-term incentive programs.
- Design and implement scalable data ingestion pipelines connecting CMC/manufacturing systems (MES, historians, LIMS, QMS, ERP, instruments) to centralized/federated data environments.
- Build connectors/adapters/integration layers for heterogeneous data formats, protocols, and latency; support batch and real-time/streaming patterns.
- Develop and maintain harmonized data models/ontologies; execute semantic mapping of fields, units, and identifiers to enterprise standards.
- Implement automated data quality controls, validation, anomaly detection; build lineage/metadata for traceability; establish monitoring/alerting/SLA practices.
- Support data 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/LLMs).
- Partner with data scientists/ML engineers/process modelers to translate model needs into scalable infrastructure.
- Contribute to PDST cloud platform evolution (lakehouse, cataloging, access control, compute); use IaC, CI/CD, automated testing; onboard new data domains/sites; provide operational support.
- Influence technical decisions through scientific rigor and demonstrated business impact.
Qualifications (Required):
- BS (or related) + 2 years, or MS + 0 years.
- Enterprise-grade experience designing/building pipelines, integration workflows, and data products.
- Expert Python; strong SQL (ANSI + dialects).
- Cloud data platforms (AWS/Azure/GCP) and tools (dbt, Spark, Airflow, Databricks, Snowflake or equivalents).
- ETL/ELT (Informatica, Talend, NiFi, AWS Glue, Azure Data Factory).
- MDM/metadata management/data cataloging for lineage and compliance.
- API/integration standards (REST/GraphQL/OData) with microservices.
- Data modeling (Erwin/PowerDesigner/dbt).
- Ownership, fit-for-purpose solution design, scientific integrity, credibility/influence, bias for impact.
Qualifications (Preferred):
- Pharma/biotech regulated life sciences manufacturing experience.
- GxP/21 CFR Part 11/data integrity familiarity.
- MES/historians (OSIsoft PI/AVEVA), LIMS, QMS, ERP exposure.
- AI/ML data infrastructure experience (feature engineering, training datasets, RAG embeddings/vector layers).
Benefits (explicitly stated):
- Paid time off (vacation, holidays, sick), medical/dental/vision insurance, 401(k); eligibility for short-term incentive programs.