This role pays less than
92%
of similar roles. Most pay
$130,268–$206,875
— the shaded band above.
At the midpoint, this role pays about
$96k
versus about
$169k
for comparable roles.
Based on 240 similar postings.
Employer
About AbbVie
AbbVie is a global biopharmaceutical company focused on discovering and delivering innovative medicines and solutions in immunology, oncology, neuroscience, and eye care. Its products include Humira, Skyrizi, and Rinvoq.
AbbVie currently has
297 open roles
on FindRole.
Listed pay typically runs
$109,500–$208,500
across 271 roles with salary data.
Associate Scientific Technical Engineer II, PDS&T CMC joins the BTS - PDST team as an AI-native engineer focused on pharmaceutical data engineering. This role involves designing and operating production-grade data pipelines to power AI, machine learning, and automation across the manufacturing and development ecosystem. You will integrate and harmonize diverse data from systems like MES, LIMS, QMS, and ERP into semantically rich assets for scientific use. Key responsibilities include building ETL/ELT pipelines, developing harmonized data models, ensuring GxP compliance, and creating feature stores for RAG and LLM applications. Required skills include expert-level Python, SQL, and experience with cloud platforms like AWS, Azure, or GCP, alongside tools such as dbt, Spark, Airflow, and Databricks. The role addresses the complexity of biological systems and regulatory requirements to accelerate product development and manufacturing decisions in a regulated pharmaceutical environment.
Design and implement scalable data ingestion pipelines from manufacturing systems like MES, LIMS, and ERP platforms.
Develop harmonized data models and ontologies to ensure consistency across diverse manufacturing sites and modalities.
Implement automated data quality controls, validation frameworks, and lineage documentation for GxP compliance.
Build and maintain production-grade data products including feature stores and vector-ready layers for AI/ML applications.
Manage infrastructure-as-code, CI/CD pipelines, and automated testing for cloud-based data platforms.
Provide operational support to ensure the uptime and reliability of production data pipelines.
Collaborate with scientists and engineers to translate complex manufacturing requirements into scalable technical architectures.
What we're looking for
Bachelor's Degree in Computer Science, Data Engineering, Information Systems, Software Engineering, Bioinformatics, or a related technical field plus 2 years of experience, or a Master's Degree.
Experience designing and building enterprise-grade data pipelines, integration workflows, and data products in multi-source environments.
Expert-level proficiency in Python for data engineering tasks including pipeline development, transformation logic, and automation.
Strong SQL skills across modern analytical and transactional databases using various platform-specific dialects.
Experience with cloud data platforms (AWS, Azure, or GCP) and tools such as dbt, Spark, Airflow, Databricks, or Snowflake.
Ability to develop ETL/ELT pipelines using tools like Informatica, Talend, Apache NiFi, or cloud-native services.
Proficiency in master data management, metadata management, data cataloging, and API development (REST, GraphQL, OData).
Experience in pharmaceutical manufacturing, GxP compliance, or building infrastructure for AI/ML programs is preferred.
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