Databricks Developer with Testing Experience

Job Title: Databricks Developer with Testing Experience

Job Type: Contract
Location: Remote/Hybrid (Client location as required)

Job Summary

We are seeking an experienced Databricks Developer with Testing Experience to design, develop, optimize, and validate large-scale data engineering solutions on the Databricks platform. The ideal candidate will have strong expertise in Databricks, Apache Spark, Python, SQL, and Azure/AWS cloud environments, along with hands-on experience in data validation, ETL testing, and automation of data quality processes.

Required Skills & Experience

• 10+ years of experience in Data Engineering, ETL Development, or Big Data technologies.
• 3+ years of hands-on experience with Databricks.
• Strong experience with Apache Spark (PySpark/Scala Spark).
• Proficiency in Python and SQL.
• Experience developing and maintaining ETL/ELT pipelines.
• Hands-on experience with data testing, ETL testing, and data validation.
• Experience validating data transformations, data migration, and reconciliation.
• Knowledge of data quality frameworks and test automation.
• Experience with cloud platforms such as Azure, AWS, or Google Cloud Platform.
• Experience with Delta Lake, Unity Catalog, and Databricks Workflows.
• Strong understanding of data warehousing concepts and dimensional modeling.
• Experience with Git, Azure DevOps, Jenkins, or CI/CD pipelines.

Preferred Skills

• Experience with Great Expectations, Deequ, or similar data quality/testing frameworks.
• Experience in Azure Data Factory (ADF), AWS Glue, or Informatica.
• Exposure to Power BI, Tableau, or other reporting tools.
• Knowledge of Agile/Scrum methodologies.
• Experience in performance tuning and optimization of Spark jobs.

Roles & Responsibilities

• Design, develop, and maintain scalable data pipelines using Databricks.
• Develop ETL/ELT solutions using PySpark and SQL.
• Perform end-to-end data validation and reconciliation between source and target systems.
• Create and execute test cases for data pipelines and transformation logic.
• Automate data quality checks and regression testing.
• Validate data accuracy, completeness, consistency, and integrity.
• Troubleshoot and resolve production data issues.
• Optimize Spark jobs for performance and scalability.
• Collaborate with business analysts, QA teams, data engineers, and stakeholders.
• Participate in code reviews, sprint planning, and production deployments.
• Maintain technical documentation and support release activities.

Nice to Have

• Databricks Certified Data Engineer Associate or Professional.
• Experience with Medallion Architecture (Bronze, Silver, Gold).
• Experience with streaming technologies such as Kafka or Spark Structured Streaming.
• Knowledge of AI/ML workflows within Databricks.
• Experience working in financial services, healthcare, or retail domains.

Keywords

Databricks, Apache Spark, PySpark, Scala, Python, SQL, Delta Lake, Unity Catalog, Data Engineering, ETL, ELT, Data Validation, ETL Testing, Data Testing, Data Quality, Great Expectations, Deequ, Azure Data Factory, AWS Glue, Azure, AWS, Google Cloud Platform, CI/CD, Jenkins, Git, Azure DevOps, Data Warehouse, Spark Optimization.