Data Engineer
Synechron (company site, opens in a new tab)BengaluruOn-siteDirect career pageEst. 18–30 LPA
Posted 10h ago
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Job description
Structured overview of role & requirements
About This Role
- Analyze and redesign enterprise-scale data pipelines, focusing on translating Omnia-based Spark pipelines into scalable cloud data solutions.
- Develop and maintain data pipelines on AWS, Snowflake, and dbt, including batch and event-driven processing using cloud-native technologies.
- Implement data quality controls, troubleshoot pipeline failures, and optimize SQL transformations for performance and accuracy.
Minimum Requirements
- Proven experience with Spark ETL, PySpark, AWS (S3, Glue, EMR, Lambda, Athena, Step Functions, SQS, IAM), Snowflake, dbt, Apache Airflow, Python, and advanced SQL.
- Experience analyzing and translating existing Omnia or similar data processing pipelines to cloud platforms.
- Work Experience Required: Not explicitly mentioned in the JD.
- Familiarity with Git, CI/CD, Jenkins and DevSecOps practices in data engineering environments.
Ideal Candidate Profile
- Experienced in enterprise data engineering with strong operational knowledge of Omnia-based Spark ETL and AWS cloud services.
- Skilled at translating complex business transformation logic into scalable cloud data pipelines and reusable framework components.
- Capable of collaborating with product owners and data designers to align technical implementation with business requirements, emphasizing reliability and performance optimization.