Senior Manager, Data Engineering

What you'll do

• Lead multiple scrum teams of data engineers to build and operate data products for Corporate Functions.
• Provide hands-on technical direction for batch and streaming data pipelines using Azure, Python, and Spark.
• Design and operate event-driven pipelines using Kafka and Spark Streaming to deliver real-time data.
• Own data quality, lineage, and stewardship practices for sensitive finance and HR data domains.
• Set priorities and manage execution across multiple teams to balance roadmap commitments and technical debt.
• Establish CI/CD, observability, and incident management practices to ensure pipeline reliability.
• Recruit, coach, and mentor engineers while fostering a culture of ownership and continuous learning.
• Build relationships with business leaders to translate requirements into clear technical roadmaps and deliverables.

What we're looking for

• Must have 2+ years of experience directly managing data engineers or technical individual contributors.
• Must have 7+ years of experience in data engineering, including multiple large and complex end-to-end projects.
• Must possess advanced Python and SQL skills with strong experience in Azure data services and distributed processing like Spark/PySpark.
• Must have hands-on experience designing or leading real-time data pipelines using Kafka, Spark Streaming, or equivalent technologies.
• Must have working knowledge of data quality frameworks, lineage, metadata management, and data governance practices.
• Must have experience managing data engineering teams and setting priorities across multiple workstreams in an agile environment.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (preferred).