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Databricks

Databricks

Infosys
Early Applicant
  • Posted 9 hours ago
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Job Description

ETL, PYSPARK, DATABRICKS, Delta Lake, Spark SQL, Data Modeling, Workflow Orchestration, Performance Tuning

Key Responsibilities:

  • Develop and maintain data pipelines and transformations using Databricks and PySpark.
  • Implement scalable ETL/ELT workflows to ingest, cleanse, and curate data for downstream analytics and reporting.
  • Optimize Spark jobs for performance and cost by tuning partitions, caching, joins, and cluster configurations.
  • Build reusable notebooks and modular code to support consistent development and easier maintenance.
  • Perform data validation, reconciliation, and quality checks to ensure accuracy and reliability of datasets.
  • Collaborate with cross-functional teams to gather requirements, clarify data definitions, and deliver aligned solutions.
  • Support deployments and production operations by troubleshooting failures, analyzing logs, and resolving incidents.
  • Contribute to documentation, coding standards, and best practices for Databricks-based development. Minimum Qualifications:
  • Bachelor's or Master's degree in BTECH, MTECH, MCA, or MSC (or equivalent).
  • 2–3 years of hands-on experience working with Databricks in data engineering or analytics engineering projects.
  • Strong experience in PySpark for building transformations and distributed data processing.
  • Solid understanding of data pipeline concepts, data modeling basics, and structured/semi-structured data handling.
  • Ability to debug and troubleshoot Spark jobs and collaborate effectively within delivery teams.
  • Experience with Spark optimization techniques and practical performance tuning in Databricks environments.
  • Familiarity with Delta Lake concepts such as ACID tables, schema evolution, and incremental processing patterns.
  • Exposure to orchestrating workflows and managing dependencies for end-to-end pipeline execution.
  • Experience working in agile delivery models with strong ownership of tasks, timelines, and quality outcomes.
  • Strong communication skills to translate requirements into implementable data solutions and clearly document outcomes.

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