Role : Senior Data Engineer - ShellKode
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.
(ref:hirist.tech)