Snowflake/Databricks Data Engineer

About the role

Build scalable enterprise data platforms and pipelines.

Domain: Data & Analytics

Client: Capgemini

Tasks

• Design and develop scalable batch and incremental data pipelines using Snowflake and Databricks.
• Build ETL/ELT workflows for structured and semi-structured data.
• Develop data models and curated datasets for analytics and reporting.
• Optimize Snowflake queries and Databricks jobs for performance and cost efficiency.
• Implement data quality checks, validation, and monitoring.
• Automate pipeline deployment, scheduling, and operational workflows.
• Troubleshoot pipeline failures and resolve data processing issues.
• Apply data governance, access control, and security practices.
• Collaborate with analysts, architects, and engineering teams.
• Maintain technical documentation and data flow processes.

Requirements

• 9+ Years
• Snowflake | Databricks | Apache Spark
• SQL | Python | ETL/ELT Pipelines
• Data Modeling | Delta Lake | Lakehouse Architecture
• Performance Optimization | Data Quality Testing
• Workflow Orchestration | Data Governance
• Strong hands-on experience with Snowflake and Databricks.
• Advanced SQL and Python programming skills.
• Experience with Apache Spark and large-scale data processing.
• Strong knowledge of ETL/ELT pipeline development.
• Experience with data modeling and performance optimization.
• Understanding of data quality, testing, and troubleshooting.
• Knowledge of secure data access and governance practices.
• Experience supporting production data engineering environments.
• Visa: H4EAD, GC, OPT, STEMOPT, GCEAD, USC
• Delta Lake and Lakehouse archite

Schedule

• Work Mode: Hybrid / Remote / On-site

Location

• New York, NY