Senior Data Engineer

Overview

Develop and maintain robust data pipelines and analytics infrastructure, with a hands-on focus on Databricks and SQL, contributing to data platform initiatives in cloud-native data solutions.

What you'll do

• Develop and deploy ETL/ELT pipelines using Databricks, PySpark, and SQL for data ingestion, transformation, and loading
• Write clean, efficient SQL and Python code for data processing, validation, and analytics
• Support data pipeline maintenance, monitor job executions, and troubleshoot data quality issues within SLA timelines
• Collaborate with Senior Engineers, Data Scientists, and Analytics teams to understand requirements and deliver solutions
• Implement data validation, error handling, and logging mechanisms to ensure pipeline reliability
• Document code, architecture decisions, and runbooks for operational excellence
• Participate in code reviews and contribute to knowledge sharing within the engineering team

What you'll need

• 5+ years of professional experience in data engineering, ETL development, or data analytics engineering
• Strong proficiency in Databricks (Spark SQL, PySpark) with real-world pipeline development experience
• Solid SQL skills including query optimization, joins, aggregations, and window functions
• Hands-on experience with Python for data processing and scripting
• Experience with cloud platforms such as Azure Data Factory, AWS Glue, or similar ETL services
• Understanding of data architecture, data modeling, and relational databases
• Strong problem-solving skills with attention to data quality and accuracy

Nice to have

• Databricks Certified Data Engineer (Associate) OR Snowflake SnowPro Core Certified OR AWS Certified Data Engineer (Associate) OR equivalent professional data engineering certification
• Experience with orchestration tools (Apache Airflow, Tidal, Control-M, etc.)
• Familiarity with cloud data warehousing (Snowflake, Redshift, BigQuery)
• Experience with Git, CI/CD pipelines, and version control
• Knowledge of Agile methodologies and experience working in cross-functional teams
• Background in data validation frameworks and data quality testing

Details

• Location: DGS India - Mumbai - Thane Ashar IT Park
• Employment type: Full time
• Contract type: Consultant
• Brand: Merkle