Data Engineer - PySpark
Talentbrew (company site, opens in a new tab)PuneOn-siteDirect career pageEst. 10–18 LPA
Posted 29d ago
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Job description
Structured overview of role & requirements
About This Role
- Build and maintain data architectures including data pipelines, data warehouses, and data lakes ensuring data integrity, accessibility, and security.
- Design and develop scalable data transformation and storage solutions using PySpark, Snowflake, and AWS Data Analytics stack (Glue, S3, Lambda, Lake formation, Athena).
- Collaborate with data scientists to build and deploy machine learning models and lead or guide team members, managing operational processing and risk within own team.
Minimum Requirements
- Hands-on experience in PySpark including DataFrames, RDD, and SparkSQL.
- Proven experience developing, testing, and maintaining applications on AWS Cloud, including AWS Data Analytics tools like Glue, S3, Lambda.
- Experience with Snowflake for scalable data storage and transformation, including data ingestion of multiple storage formats (Parquet, Iceberg, JSON, CSV).
- Work Experience Required: Should have worked on at least two major project implementations; Location Requirement: Based in Pune.
Ideal Candidate Profile
- Strong technical expertise with cloud-based enterprise data warehousing and multiple data platforms including Snowflake and NoSQL environments.
- Ability to engage stakeholders to elicit and translate requirements into ETL solutions and provide infrastructure-related solutions independently or collaboratively.
- Experience leading or supervising teams, managing end-to-end operational accountability, embedding risk controls, and advising on data governance and lineage tools (preferred but not mandatory).