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Job Description & How to Apply Below
Role Overview
The Client Data Engineer will be responsible for the design, development, validation, optimization, and ongoing ownership of data solutions primarily using AWS and Databricks . The role will work closely with internal teams, business SMEs, architects, governance teams, Power BI/analytics teams, and implementation partners.
The ideal candidate should have 8+ years of experience in data engineering, ETL/ELT, and data integration , with strong hands-on expertise in Databricks, AWS, SQL, Python, PySpark, and Spark .
Key Responsibilities
Design, develop, and support AWS and Databricks data pipelines using SQL, Python, PySpark, and Spark.
Develop and maintain Bronze, Silver, and Gold data layers using Databricks and Delta Lake.
Work with source-system data, business rules, mappings, and integration requirements.
Review and validate data solutions delivered by implementation partners.
Perform data profiling, reconciliation, testing, and troubleshooting.
Support data quality, metadata, lineage, and Unity Catalog activities.
Optimize Databricks pipelines and queries for performance, scalability, and cost efficiency.
Participate in code reviews, CI/CD, deployment, and production support.
Maintain technical documentation and support knowledge transfer to internal teams.
Collaborate closely with BI and analytics teams on downstream reporting and data requirements.
Support integration with Tableau and Power BI for reporting and analytics use cases.
Required Skills
8+ years of experience in data engineering, ETL/ELT, or data integration.
Strong hands-on experience with Databricks .
Strong experience with AWS data services and cloud-based data platforms .
Strong SQL and Python skills.
Strong experience with PySpark / Apache Spark .
Experience designing and implementing data pipelines and data transformation frameworks.
Strong understanding of data integration, transformation, reconciliation, and data quality.
Strong analytical, troubleshooting, and communication skills.
Preferred Skills
Databricks, Delta Lake, and Unity Catalog .
AWS Databricks / Databricks on AWS experience.
Medallion/Lakehouse architecture.
Experience with Tableau reporting and Power BI .
Git, CI/CD, and Dev Ops practices.
Experience with data governance, metadata, lineage, and data quality frameworks.
Databricks certification is a plus.
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