Senior Data Engineer

Overview

Senior Data Engineer building resilient, production-grade data pipelines and data products, turning raw data into reliable datasets for business use.

What you'll do

• Build and maintain high-throughput ETL/ELT pipelines ingesting data into a Lakehouse.
• Use dbt for transformation and PySpark for heavy lifting with modular, reusable code.
• Implement data observability by defining Data SLAs and monitoring for data drift or pipeline failures.
• Prepare “feature-ready” datasets for BI team and Data Scientists.
• Optimize SQL and Spark query plans to reduce cost and latency.
• Enable local development workflows for SQL transformations using DuckDB and advocate embedded/local analytics patterns.

What you'll need

• 5+ years in Data Engineering.
• Expert-level proficiency in Python, SQL, and PySpark.
• Hands-on experience with Databricks (Delta Lake) or Snowflake.
• Advanced experience with dbt, including version control, testing, and documentation.
• Experience with Apache Airflow or Prefect building complex, idempotent DAGs.
• Comfort with Terraform or CloudFormation for data infrastructure.

Details

• Work mode: Remote.
• Location: Greater Noida, India.