CMC Data Engineer II: AI/ML Data Pipelines

BioSpace

North Chicago (IL)

On-site

USD 150,000 - 185,000

Full time

14 hours ago
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Benefits offered by this job

Medical/dental/vision insurance
Paid time off
401(k)

Job summary

AbbVie is seeking a highly technical Data Engineer within the PDST to design, build, and operate production-grade data pipelines powering AI/ML and analytics across CMC and manufacturing systems. You will harmonize data from MES, LIMS, QMS, ERP, and historians into trusted data assets used by data scientists and process engineers.

The role emphasizes data quality, governance, and scalable cloud-based platform improvements, aligning with GxP and 21 CFR Part 11 standards while enabling rapid

Qualifications

  • Bachelor's or Master's degree in a technical field with hands-on data engineering experience.

Responsibilities

  • Design scalable data ingestion pipelines connecting MES, LIMS, QMS, ERP, historians, and instrument data sources.
  • Build connectors and integration layers for heterogeneous data formats and protocols.
  • Support batch and real-time data patterns and ensure data reliability in production.
  • Develop harmonized data models and ontologies for enterprise data.
  • Deliver governed, reusable data products for AI/ML and analytics.

Skills

Data ingestion
Data modeling
ETL/ELT
Data quality
MLOps

Education

Bachelor's Degree in Computer Science or related
Master's Degree in related field

Tools

Python
SQL
dbt
Spark
Airflow
Databricks
Snowflake
AWS
Azure
GCP
Informatica
Talend
NiFi

Job description

AbbVie is seeking a highly technical Data Engineer within the PDST to design, build, and operate production-grade data pipelines powering AI/ML and analytics across CMC and manufacturing systems. You will harmonize data from MES, LIMS, QMS, ERP, and historians into trusted data assets used by data scientists and process engineers.

The role emphasizes data quality, governance, and scalable cloud-based platform improvements, aligning with GxP and 21 CFR Part 11 standards while enabling rapid

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