Mphasis
Base pay range: $120,000.00/yr - $130,000.00/yr
Job Description We are looking for a Senior Data Engineer with strong experience in Databricks, PySpark, and modern Data Warehouse systems. The ideal candidate can design, build, and optimize scalable data pipelines and work closely with analytics, product, and engineering teams.
Key Responsibilities
Design and build ETL/ELT pipelines using Databricks and PySpark
Develop and maintain data models and data warehouse structures (dimensional modeling, star/snowflake schemas)
Optimize data workflows for performance, scalability, and cost
Work with cloud platforms (Azure/AWS/GCP) for storage, compute, and orchestration
Ensure data quality, reliability, and security across pipelines
Collaborate with cross-functional teams (Data Science, BI, Product)
Write clean, reusable code and follow engineering best practices
Troubleshoot issues in production data pipelines
Required Skills
Strong hands-on skills in Databricks, PySpark, and SQL
Experience with data warehouse concepts, ETL frameworks, batch/streaming pipelines
Solid understanding of Delta Lake and Lakehouse architecture
Experience with at least one cloud platform (Azure preferred)
Experience with workflow orchestration tools (Airflow, ADF, Prefect, etc.)
Nice to Have
Experience with CI/CD for data pipelines
Knowledge of data governance tools (Unity Catalog or similar)
Exposure to ML data preparation pipelines
Soft Skills
Strong communication and documentation skills
Ability to work independently and mentor others
Problem-solver with a focus on delivering business value
Seniority Level Mid-Senior level
Employment Type Full-time
Job Function Finance, Information Technology, and Manufacturing
Industries IT Services and IT Consulting
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Job Description We are looking for a Senior Data Engineer with strong experience in Databricks, PySpark, and modern Data Warehouse systems. The ideal candidate can design, build, and optimize scalable data pipelines and work closely with analytics, product, and engineering teams.
Key Responsibilities
Design and build ETL/ELT pipelines using Databricks and PySpark
Develop and maintain data models and data warehouse structures (dimensional modeling, star/snowflake schemas)
Optimize data workflows for performance, scalability, and cost
Work with cloud platforms (Azure/AWS/GCP) for storage, compute, and orchestration
Ensure data quality, reliability, and security across pipelines
Collaborate with cross-functional teams (Data Science, BI, Product)
Write clean, reusable code and follow engineering best practices
Troubleshoot issues in production data pipelines
Required Skills
Strong hands-on skills in Databricks, PySpark, and SQL
Experience with data warehouse concepts, ETL frameworks, batch/streaming pipelines
Solid understanding of Delta Lake and Lakehouse architecture
Experience with at least one cloud platform (Azure preferred)
Experience with workflow orchestration tools (Airflow, ADF, Prefect, etc.)
Nice to Have
Experience with CI/CD for data pipelines
Knowledge of data governance tools (Unity Catalog or similar)
Exposure to ML data preparation pipelines
Soft Skills
Strong communication and documentation skills
Ability to work independently and mentor others
Problem-solver with a focus on delivering business value
Seniority Level Mid-Senior level
Employment Type Full-time
Job Function Finance, Information Technology, and Manufacturing
Industries IT Services and IT Consulting
#J-18808-Ljbffr