Job Role – Data Engineer
Location – Noida (Hybrid)
Key Responsibilities
• Build and optimize end-to-end ETL/ELT pipelines for structured and semi-structured data using Python,
PySpark and Databricks.
• Automate complex workflows using Apache Airflow and manage cloud-native services (AWS Glue/Lake
Formation or Azure Data Factory).
• Implement real-time ingestion layers using Kafka, AWS MSK, or Kinesis to ensure low-latency data
availability.
• Maintain and query relational databases (SQL Server, Oracle) while ensuring high data integrity and
performance.
• Manage code versions via Git and contribute to CI/CD pipelines for automated cloud resource
deployment.
Technical Requirements
• 4+ years of professional experience in a Data Engineering role.
• Strong proficiency in Python and SQL.
• Hands-on experience with Spark/Databricks for large-scale processing.
• Proven experience in either AWS (Glue, Kinesis, Lake Formation) or Azure (ADF, Event Hubs), GCP
(BigQuery).
• Ability to translate technical pipeline architecture into clear business value for stakeholders.
Good to Have
• Experience with Geospatial data formats and algorithms.
• Experience with AI/ML.
• Experience with Trino SQL.
• Familiarity with NoSQL environments (ElasticSearch, Graph Databases).
• Web fundamentals: Basic knowledge of React/TypeScript for data-heavy applications
…