Azure Databricks Data Engineer
Job Title: Senior Azure Databricks Data Engineer
Experience: 9-15 Years of IT Experience
Location: Warren, MI (Hybrid)
Job Summary:
We are seeking a skilled Databricks Engineer with minimum of 5+ years of hands-on in Databricks who can design, develop, and optimize scalable data platforms and analytics solutions using the Databricks Lakehouse Platform. The ideal candidate will have expertise in data engineering, ETL/ELT development, cloud technologies preferably Azure, and big data processing to support enterprise analytics and AI initiatives.
Key Responsibilities:
- Design, develop, and maintain data pipelines using Databricks, Apache Spark, and cloud-native services.
- Build and optimize ETL/ELT workflows for large-scale structured and unstructured data.
- Develop data models and implement data quality, validation, and governance frameworks.
- Integrate data from multiple sources into a unified Lakehouse architecture.
- Optimize Spark jobs and Databricks workloads for performance, scalability, and cost efficiency.
- Implement security controls, access management, and data governance using Unity Catalog.
- Collaborate with business, analytics, and AI/ML teams to deliver trusted data products.
- Monitor, troubleshoot, and resolve data pipeline issues.
- Support CI/CD, DevOps, and infrastructure automation practices.
- Maintain technical documentation and best practices.
- Required Technical SkillsCore Technologies
- Databricks Lakehouse Platform
- Apache Spark / PySparkDelta LakeSQLPythonData EngineeringETL / ELT Development
- Data Modeling
- Data Warehousing
- Data Quality & Validation
- Streaming & Real-Time Processing
- Governance & Security
- Unity Catalog
- Data Lineage
- Row-Level Security
- Access Control & Compliance
- Data Governance Frameworks
- Cloud & DevOpsAzure / AWS / GCPTerraformGitHub Actions / Azure DevOpsCI/CD Pipelines
- Analytics & AISemantic LayersData ProductsBI Platforms
- Machine Learning Support
- Generative AI & RAG Architectures
Required Qualifications:
Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related field.9-15 years of experience in Data Engineering and Data Warehousing.
Minimum 5+ years of hands-on experience with Azure Data Engineering technologies.
Minimum 4+ years of hands-on experience with Azure Databricks and Spark ecosystem.
Strong understanding of data lake, lakehouse, and cloud-native architecture patterns.
Experience in handling large-scale structured and unstructured datasets.
Strong analytical, problem-solving, and troubleshooting skills.
Preferred Qualifications:
Microsoft Certified: Azure Data Engineer Associate (DP-203).Databricks Certified Data Engineer Associate/Professional.
Experience with Snowflake, Power BI, or Microsoft Fabric.
Experience in real-time streaming solutions using Kafka/Event Hubs.
Exposure to Data Governance and Master Data Management initiatives.
Soft SkillsStrong stakeholder management and communication skills.
Ability to lead technical initiatives and drive architecture discussions.
Experience working in Agile/Scrum environments.
Excellent documentation and presentation skills.
Strong mentoring and team leadership abilities.
Nice to Have:
Microsoft FabricPower BIAzure Event HubsKafkaMachine Learning data pipelines Data Governance tools such as Purview