PuneOn-siteDirect career pageEst. 8–20 LPA
Posted 1h ago
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Job description
Structured overview of role & requirements
About This Role
- Develop and support enterprise-grade production data pipelines.
- Build batch ETL and lakehouse solutions using Azure, Databricks, Spark, and Delta Lake.
- Address pipeline performance and reliability through distributed-processing techniques, exception handling, CI/CD, and infrastructure as code.
Minimum Requirements
- Work Experience Required: Not explicitly mentioned in the JD.
- Technical skills listed: Python, PySpark, Spark SQL, Databricks, Azure, REST APIs, ETL pipelines, Delta Lake/lakehouse architecture, ADLS, Terraform/IaC, and CI/CD.
- Spark fundamentals include partitioning, caching, distributed processing, and performance enhancement; batch processing and exception handling are also listed.
Ideal Candidate Profile
- Best fit for someone focused on developing and supporting production data pipelines in enterprise environments.
- Likely shortlist signal: practical experience with Azure and Databricks-based batch ETL, Spark performance, and lakehouse patterns.
- A profile that can work across pipeline development, operational support, and deployment automation aligns with the listed responsibilities and tools.