Design, develop, and optimize data pipelines, data integration frameworks, and metadata-driven architectures for Manufacturing and Operations use cases
Job Summary
Design, develop, and optimize data pipelines, data integration frameworks, and metadata-driven architectures for Manufacturing and Operations use cases.
Ingest and transform structured and unstructured data from various sources, ensuring data integrity, accuracy, and consistency.
Work in an Agile and Scaled Agile (SAFe) environment, collaborating with cross-functional teams to deliver incremental value and support continuous improvement.
Matching Summary
Design, develop, and optimize data pipelines, data integration frameworks, and metadata-driven architectures for Manufacturing and Operations use cases.
Skills & Requirements
Must-have
Databricks, PySpark, Scala, SQL
Big data processing, distributed computing
Data modeling, governance frameworks
AWS services, hybrid cloud environments
ETL/ELT data pipelines
Agile and Scaled Agile (SAFe) environment
Nice-to-have
AI assisted code development
Biotechnology or pharma industry experience
Writing APIs for data access
SQL/NoSQL, vector databases
Software engineering best practices
Manufacturing data sources (SCADA, Data Historians)
Key Requirements
5 to 9 years of Computer Science, IT or related field experience