Technical Lead – Azure Databricks
Grand Rapids, MI · HybridFull-timePosted 1 day agoStill listed today
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Job overview
Celebal Technologies seeks a hands-on Technical Lead to architect and deliver enterprise migrations from legacy data warehouses and processing systems to Azure Databricks Lakehouse. The role leads technical strategy, scalable batch and streaming pipeline design, governance, security, and performance optimization. It also guides a team of 5–10 data engineers and collaborates with architecture, project, and business stakeholders to deliver migration work.
Skills & qualifications
Skills
Qualifications
Full job description
Technical Lead – Azure Databricks
Location: Grand Rapids, MI (Hybrid) Employment Type: Full-time Experience Level: 8–15 Years Department: Data & Analytics
About the Role We are seeking an experienced and hands-on Technical Lead – Azure Databricks to architect and drive large-scale, enterprise data platform migrations. In this role, you will lead the technical strategy, design, and execution of migrating legacy data warehouses and processing systems (e.g., on-premises Hadoop, Teradata, Netezza, or legacy SQL) to a modern, scalable Lakehouse architecture powered by Azure Databricks. You will act as the bridge between enterprise architecture, data engineering teams, and key stakeholders, ensuring robust delivery, performance optimization, and adherence to cloud security standards.
Key Responsibilities
- Migration Strategy & Execution: Lead end-to-end design, planning, and implementation of legacy platform migrations to Azure Databricks using the Medallion Architecture (Bronze/Silver/Gold).
- Architecture & Pipeline Engineering: Design highly scalable batch and streaming data pipelines using PySpark/Scala, Spark SQL, Delta Lake, and Delta Live Tables (DLT).
- Data Integration & Orchestration: Build robust orchestration workflows using Azure Data Factory (ADF), Databricks Workflows, and Event Hubs/Kafka.
- Performance Tuning: Optimize Databricks clusters, query performance, compute utilization, partition pruning, and Delta Lake optimizations (Z-Ordering, compaction, liquid clustering).
- Governance & Security: Implement Unity Catalog for fine-grained access control, data lineage, auditing, and data masking across Azure environments.
- Technical Leadership & Mentorship: Guide, mentor, and conduct code/architecture reviews for a team of 5–10 data engineers, establishing best practices in CI/CD, unit testing, and Databricks Asset Bundles (DABs).
- Stakeholder Management: Collaborate with project managers, solution architects, and business stakeholders to identify technical blockers, scope sprints, and deliver business value on schedule.
Required Technical Skills & Qualifications
- Experience: 8–15 years of hands-on data engineering experience, with at least 3+ years leading technical teams on enterprise Azure Databricks implementations.
- Core Databricks Expertise: Deep knowledge of Apache Spark internals, Delta Lake, Delta Live Tables, Unity Catalog, and cluster performance tuning.
- Azure Data Ecosystem: Strong expertise in Azure Data Factory, Azure Data Lake Storage Gen2 (ADLS Gen2), Azure Key Vault, Azure Synapse, and Azure DevOps (CI/CD pipelines).
- Migration Experience: Proven track record of delivering at least one end-to-end large-scale migration project (e.g., Hadoop/Cloudera, Teradata, Oracle, or SQL Server to Azure Databricks Lakehouse).
- Programming Languages: Proficiency in Python / PySpark and advanced SQL (experience with Scala is a strong plus).
- Data Modeling: Solid foundation in dimensional modeling (Star/Snowflake schema), modern Lakehouse modeling, and historical data reconciliation strategies.
- DevOps & Automation: Experience setting up CI/CD using Azure DevOps or GitHub Actions, Infrastructure as Code (Terraform/Bicep), and automated testing frameworks.
Preferred Qualifications & Certifications Certifications:
- Databricks Certified Data Engineer Professional
- Microsoft Certified: Azure Data Engineer Associate (DP-203)
- Experience with automated schema migration, data reconciliation, and dual-run validation tooling.
- Familiarity with data observability, monitoring (Databricks System Tables, Azure Monitor/Log Analytics), and cost optimization frameworks (FinOps).
How this job compares
Set against the 2,849 open Data Engineering jobs on Olive Jobs, counted November 4, 2026.
- Pay
- This postingNot listed
- Michigan median$105–208K/yr34 salary ranges
- US median$49–58/hr88 hourly ranges
- Openings
- Olive Jobs lists 39 open Data Engineering jobs in Michigan and 2,849 across the US. 8% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 8 years of experience; Data Engineering postings that state a minimum ask for 5 years at the median (2,427 postings).
- Education
- 1,009 of the 2,849 open Data Engineering jobs (35%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 4, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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