This role blends people leadership with deep, hands-on technical contribution. As a Data Engineering Manager, you will partner closely with senior leaders to design, build, and evolve cloud-based data solutions that power analytics, reporting, and advanced data initiatives.
You are a working manager who stays close to the technology—solving complex data challenges, reviewing critical implementations, and setting engineering standards through direct involvement. You will play a key role in shaping the technical direction of the data platform while mentoring and growing a high-performing engineering team.
What You’ll Do
Lead the design and delivery of cloud-native data engineering solutions supporting analytics and data science use cases Serve as a hands‑on technical leader, contributing directly to complex Databricks implementations and architectural decisions Drive the evolution of a modern cloud data platform, including data lake and lakehouse architectures Establish and enforce best practices for data modeling, ELT pipelines, orchestration, and performance optimization Ensure the reliability, scalability, and security of data platforms and pipelines Build, mentor, and retain a strong team of data engineers Collaborate with business and technical stakeholders to align data strategy with organizational priorities Technical Experience & Skills
Strong experience with Azure-based data platforms, including Azure Databricks, Azure Data Lake, Fabric, and Data Factory Deep, hands‑on expertise with Databricks notebooks, workflows, and asset bundles Proficiency in Python, PySpark, and SQL Experience designing modern data architectures, including lakehouse, streaming, and data mesh patterns Solid understanding of data governance, security, and performance tuning best practices
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Lead the design and delivery of cloud-native data engineering solutions supporting analytics and data science use cases Serve as a hands‑on technical leader, contributing directly to complex Databricks implementations and architectural decisions Drive the evolution of a modern cloud data platform, including data lake and lakehouse architectures Establish and enforce best practices for data modeling, ELT pipelines, orchestration, and performance optimization Ensure the reliability, scalability, and security of data platforms and pipelines Build, mentor, and retain a strong team of data engineers Collaborate with business and technical stakeholders to align data strategy with organizational priorities Technical Experience & Skills
Strong experience with Azure-based data platforms, including Azure Databricks, Azure Data Lake, Fabric, and Data Factory Deep, hands‑on expertise with Databricks notebooks, workflows, and asset bundles Proficiency in Python, PySpark, and SQL Experience designing modern data architectures, including lakehouse, streaming, and data mesh patterns Solid understanding of data governance, security, and performance tuning best practices
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