Scientific Technical Engineer - PDS&T; CMC (AI/Data Engineering)

Location: North Chicago, Illinois, United States

Salary: $96,500–$183,500 per year

Company

hirify.global develops medicines and healthcare solutions across immunology, oncology, neuroscience, aesthetics, and other therapeutic areas.

What you will do

• Design and operate scalable batch and real-time data pipelines connecting MES, process historians, LIMS, QMS, ERP, and instrument platforms.
• Develop harmonized data models, ontologies, semantic mappings, and governed data products for CMC and manufacturing data.
• Implement data quality controls, validation, anomaly detection, lineage, metadata, observability, and SLA monitoring.
• Enable AI/ML programs through curated datasets, feature stores, vector-ready data layers, and reliable model inputs.
• Contribute to cloud lakehouse architecture, data cataloging, access control, infrastructure-as-code, CI/CD, and automated testing.
• Partner with scientists, engineers, quality, regulatory, and data science stakeholders to guide technical decisions.

Requirements

• Bachelor’s degree in computer science, data engineering, information systems, software engineering, bioinformatics, or a related technical field with 6+ years of experience; alternatively, a master’s degree with 5+ years or a PhD.
• Hands-on experience building enterprise-grade data pipelines, integration workflows, and data products in complex multi-source environments.
• Expert Python and strong SQL skills, including experience with analytical and transactional databases.
• Experience with AWS, Azure, or GCP and modern data tools such as dbt, Spark, Airflow, Databricks, Snowflake, Informatica, Talend, Apache NiFi, AWS Glue, or Azure Data Factory.
• Experience with MDM, metadata management, data cataloging, APIs, data integration, REST, GraphQL, OData, and microservices architectures.
• Ability to work with GxP requirements, 21 CFR Part 11, data integrity, and regulated life sciences environments.

Nice to have

• Experience with biologics manufacturing, CMC development, technology transfer, process characterization, or commercial process validation.
• Knowledge of MES, historians such as OSIsoft PI/AVEVA, LIMS, QMS, ERP, data mesh, data fabric, graph databases, knowledge graphs, or ontology frameworks.
• Experience building feature engineering pipelines, training datasets, or vector and embedding layers for RAG architectures.

Culture & Benefits

• Work on AI-native data engineering programs across clinical, commercial, and lifecycle-stage biologics development.
• Direct impact on regulatory submissions, commercial readiness, manufacturing decisions, and medicine supply.
• Benefits include paid vacation, holidays, sick leave, medical, dental, and vision insurance, and a 401(k) plan for eligible employees.
• Eligibility for short-term incentive programs.