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Location: Alpharetta, GA (Preferred) | Frisco, TX | Berkeley Heights, NJ
Contract Role
Job Summary
We are seeking a skilled Azure Databricks Data Engineer to design, build, and maintain scalable data pipelines and lakehouse architectures on Azure. The ideal candidate will have strong experience in Databricks, PySpark, Spark SQL, and Azure data services with a focus on building high-performance ETL/ELT pipelines and optimizing big data workloads.
Key Responsibilities
Design, build, and maintain scalable data pipelines using Azure Databricks, PySpark, Spark SQL, and Delta Lake.
Develop high-performance ETL/ELT workflows to process structured and unstructured datasets.
Optimize Spark clusters, jobs, and queries to improve performance and reduce cloud costs.
Develop and maintain data lakehouse architecture on Azure Data Lake Storage (ADLS).
Build and orchestrate data workflows using Azure Data Factory (ADF) or Azure Synapse Pipelines.
Implement CI/CD pipelines for Databricks notebooks using Git integration and DevOps pipelines.
Ensure data quality, lineage, and governance using tools such as SQL, Delta Live Tables, and Unity Catalog.
Collaborate with product, analytics, and engineering teams to understand business data requirements and deliver solutions.
Implement data security and governance best practices, including RBAC, tokenization, and workspace-level permissions.
Required Skills & Qualifications
Strong experience with Azure Databricks, PySpark, and Spark SQL.
Hands-on experience with Delta Lake and lakehouse architecture.
Experience with Azure Data Lake Storage (ADLS).
Experience building and orchestrating pipelines with Azure Data Factory (ADF) or Azure Synapse.
Knowledge of CI/CD pipelines, Git, and DevOps integration for Databricks.
Strong SQL and data modeling skills.
Understanding of data governance, lineage, and security frameworks.
Experience working with large-scale distributed data systems.
Sprachkenntnisse
- English
Hinweis für Nutzer
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