Data Engineering Manager

What you'll do

• Lead, mentor, and develop a team of data engineers while fostering high engineering standards and accountability.
• Design, build, and support scalable data pipelines and products for analytics, AI/ML, and commercial use cases.
• Translate ambiguous business requirements from stakeholders into technical specifications and actionable execution plans.
• Provide architectural leadership for pipeline orchestration, distributed processing, and cloud-native platform integration.
• Manage team delivery, including capacity planning, prioritization, and execution of multiple concurrent data initiatives.
• Drive operational excellence through monitoring, troubleshooting, incident response, and automated process improvements.
• Develop and optimize reusable data assets to support business-critical workflows across global platforms.
• Establish and evolve data engineering standards and best practices across the organization.

What we're looking for

• 6+ years of experience in data engineering, analytics engineering, or data platform development.
• 2+ years of experience leading or managing engineering teams.
• Experience designing and operating scalable data pipelines using Spark, Kafka, Snowflake, Hadoop, or similar technologies.
• Experience with cloud-native data engineering and modern ETL/ELT solutions (Informatica/IICS preferred).
• Advanced SQL and data modeling skills with working knowledge of Python; Scala or Java is a plus.
• Experience with batch, near real-time, and streaming architectures including warehouse, lake, and lakehouse concepts.
• Bachelor’s or Master’s degree in Computer Science, Engineering, STEM, Business, or a related field, or equivalent practical experience.
• Experience in life sciences, healthcare, or pharmaceutical industries (preferred).