Senior Data Engineer - Tech Consulting

Senior Consultant - Tech Consulting - FS - CNS - TC - Platforms - Hyderabad

APAC Data Engineering Team Skill Requirements

Data Engineer

Role

Build and maintain the future of Vanguard’s data platform on Databricks by designing and developing robust, scalable pipelines. Contribute to a validated, self-serve data ecosystem that supports analytics and business insights.

Base Skillsets

• Hands-on experience with Databricks (Spark, Delta Lake).
• Strong Python, Pyspark and SQL skills.
• Building and maintaining scalable ETL/ELT pipelines in AWS.
• Understanding of Medallion Architecture and data validation.
• Familiarity with orchestration tools (e.g., Airflow, Databricks Workflows).
• Experience and comfort with modelling with Kimball-style modelling (Star schemas).

Preferable Skillsets

• Experience with CI/CD and infrastructure-as-code (Terraform).
• Exposure to Delta Live Tables and Unity Catalog.
• Knowledge of DataOps practices and data quality frameworks.

Responsibilities

• Design and deploy Databricks infrastructure using approved patterns.
• Develop and maintain ingestion pipelines via the Common Ingestion Framework.
• Collaborate with Product Managers and Business Analysts to validate data quality and ensure integrity.
• Define, document, and build tests within the Testing Framework defined within the program, including the Enterprise solution and the local, notebook-based process.
• Implement CI/CD for data pipelines and enforce best practices in testing and documentation.
• Monitor pipeline performance, troubleshoot issues, and optimize for cost and scalability.
• Document solutions and share knowledge with the engineering team.
• Support migration from existing infrastructure to Databricks.

Requisition Id : 1637235

 

APAC Data Engineering Team Skill Requirements

Data Engineer

Exp level: 5 yrs Hyderabad location

Role

Build and maintain the future of Vanguard’s data platform on Databricks by designing and developing robust, scalable pipelines. Contribute to a validated, self-serve data ecosystem that supports analytics and business insights.

Base Skillsets

• Hands-on experience with Databricks (Spark, Delta Lake).
• Strong Python, Pyspark and SQL skills.
• Building and maintaining scalable ETL/ELT pipelines in AWS.
• Understanding of Medallion Architecture and data validation.
• Familiarity with orchestration tools (e.g., Airflow, Databricks Workflows).
• Experience and comfort with modelling with Kimball-style modelling (Star schemas).

Preferable Skillsets

• Experience with CI/CD and infrastructure-as-code (Terraform).
• Exposure to Delta Live Tables and Unity Catalog.
• Knowledge of DataOps practices and data quality frameworks.

Responsibilities

• Design and deploy Databricks infrastructure using approved patterns.
• Develop and maintain ingestion pipelines via the Common Ingestion Framework.
• Collaborate with Product Managers and Business Analysts to validate data quality and ensure integrity.
• Define, document, and build tests within the Testing Framework defined within the program, including the Enterprise solution and the local, notebook-based process.
• Implement CI/CD for data pipelines and enforce best practices in testing and documentation.
• Monitor pipeline performance, troubleshoot issues, and optimize for cost and scalability.
• Document solutions and share knowledge with the engineering team.
• Support migration from existing infrastructure to Databricks.

 

 

Experience Level

Senior Level