Senior Data Engineer

Role Summary

The Senior Data Engineer will contribute to the design, development, and optimization of scalable data systems that support analytics, artificial intelligence (AI), machine learning (ML), and business intelligence (BI) initiatives. They will participate in the creation of robust, efficient, and automated data pipelines while implementing advanced data integration and governance solutions.

Responsibilities

• Design and maintain scalable data pipelines, integrate diverse systems, and support AI/ML workflows while ensuring data quality, governance, and performance.
• Build and optimize ETL/ELT pipelines for systems like MES, ERP, LIMS, EAMS, and QMS using tools like Talend, Informatica, Boomi, and AWS Glue.
• Automate workflows for analytics, AI, and ML, ensuring reliability and high performance.
• Integrate structured and unstructured data into centralized storage systems (data lakes, warehouses).
• Establish data governance frameworks for quality, security, and compliance.
• Collaborate with cross-functional teams to prepare datasets for AI/ML, support feature engineering, and enable real-time data streaming.
• Monitor and resolve data quality issues, perform debugging, and ensure system scalability.
• Participate in Agile processes and share best practices to improve tools and workflows.

Qualifications

• Required: BS/BA in Computer Science, Bioinformatics, or related field.
• Required: Data Engineer: 2 years of relevant experience; Senior Data Engineer: 5 years of relevant experience.
• Preferred: Familiarity with regulated industries.

Skills

• Experience with GenAI to support own work and ETL concepts and tools
• Knowledge of SQL, Python & Microsoft technologies (Azure, Power BI)
• Knowledge of AWS services (S3, Redshift, Glue, Lambda) is beneficial
• CI/CD practices using Jenkins, Git, or Azure DevOps
• Agile development methodologies; tools like Jira or Trello
• Understanding of data governance concepts; good communication skills; willingness to learn and grow