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Generalist Data Engineer role, mid-level, metro locations and broad tech stack increase competition.
Data engineering skills (ETL, Snowflake, PySpark, AWS) are broadly transferable across industries.
Multiple mandatory technologies (Snowflake, Glue, PySpark, AWS, Golang/Python) enforce strict technical filters.
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Develop and manage data engineering workflows using ETL/ELT processes with Snowflake, AWS Glue, and PySpark.
Build and maintain backend services using Golang and Python integrating with AWS cloud services.
Implement streaming and messaging solutions using Kafka, RabbitMQ, and support CI/CD pipelines for automated deployments.
Proficient in Data Engineering with experience in ETL/ELT development using Snowflake, AWS Glue, PySpark, Python, and SQL.
Experience with backend development using Golang and Python.
Familiarity with AWS cloud services and related DevOps CI/CD tools such as GitHub Actions, GitLab CI, Jenkins, or AWS Code Pipeline.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building scalable data pipelines in a cloud environment, preferably AWS.
Skilled at integrating data streaming and messaging technologies like Kafka and RabbitMQ.
Comfortable managing and automating deployment workflows using multiple CI/CD tools across development and production environments.