Sr Data Engineer

Experience:

• 3+ years of experience working in data engineering or big data environments.
  

• Experience working with services like EMR, Glue, Redshift within AWS, Snowflake, and Databricks
  

• Hands-on experience with AWS, Spark, Python, and SQL
  

• Solid understanding of data modeling and data warehouse design principles
  

• Experience with distributed data frameworks such as Spark (Core, SQL, Streaming) or Flink
  

• Hands-on experience with Snowflake or Databricks
  

• Experience working on setting up data warehouses/ lake or lakehouse platforms end-to-end
  

• Industry knowledge in Retail, Logistics, FSI, or Manufacturing would be an added advantage
  

Roles & Responsibilities:

• Develop, maintain, and optimize ETL pipelines for batch and streaming data
  

• Work with data architects to implement scalable data models and warehouse structures
  

• Write efficient SQL and PySpark code for data transformation and analytics
  

• Support data quality, governance, and monitoring processes
  

• Collaborate with business and analytics teams to understand data requirements and ensure timely data delivery
  

• Participate in performance tuning and troubleshooting of data workflows
  

• Contribute to documentation, standards, and automation across data engineering projects
  

• Collaborate with cross-functional teams to ensure seamless data delivery and alignment with business goals
  

Key Skills:

• Technologies: AWS, Spark, Python, SQL, Airflow, Kafka, Snowflake, Databricks
  

• Frameworks: Spark Core, Spark SQL, Spark Streaming/Flink
  

• Soft Skills: Customer communication, Team coordination, problem-solving, Ownership