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Zorba AI Linkedin · Posted yesterday

Databricks Engineer

India

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Job Overview

We are looking for an experienced Databricks Engineer with a strong background in Informatica PowerCenter, ETL, Data Warehousing, Data Modeling, and modern Data Lake architectures.

The ideal candidate will have strong hands-on experience building and optimizing data pipelines using Databricks, PySpark, Spark SQL, and Delta Lake, along with prior experience in Informatica PowerCenter. The role requires someone who can independently manage end-to-end data engineering activities across ingestion, transformation, modeling, quality, and analytics.

Key Skills / Essential Experience

  • 8+ years of experience in data engineering / large-scale data management.
  • Strong hands-on experience with Databricks.
  • Excellent experience with PySpark / Spark / Spark SQL.
  • Strong knowledge of Delta Lake and modern Data Lake architectures.
  • Extensive experience in ETL/ELT development.
  • Hands-on experience with Informatica PowerCenter, including development, support, migration, and modernization.
  • Strong understanding of Data Warehousing and Data Lake concepts.
  • Expertise in Data Modeling, including:
    • Dimensional Modeling
    • Star Schema
    • Snowflake Schema
  • Experience working in a Microsoft Azure Data Platform environment.
  • Good SQL programming skills.
  • Strong understanding of data ingestion, transformation, integration, and processing.
  • Experience with data quality, governance, and performance optimization.
Key Responsibilities

  • Design, develop, and optimize scalable data pipelines using Databricks and PySpark.
  • Develop and maintain robust ETL/ELT workflows for data ingestion, transformation, and loading.
  • Leverage Informatica PowerCenter expertise for ETL migration, modernization, integration, and support initiatives.
  • Design and implement scalable Data Lake and Data Warehouse solutions.
  • Work extensively with Delta Lake, Spark SQL, and PySpark.
  • Develop efficient data models to support analytics and reporting requirements.
  • Implement Dimensional, Star, and Snowflake schemas as required.
  • Perform data transformation and optimization across large datasets.
  • Ensure data pipelines meet performance, scalability, reliability, and data quality requirements.
  • Implement data governance and quality best practices.
  • Collaborate with business analysts, data architects, developers, and other technical stakeholders to understand requirements and deliver robust solutions.
  • Troubleshoot and resolve data pipeline, ETL, and performance issues.
  • Participate in Agile development methodologies, sprint planning, reviews, and daily stand-ups.
  • Contribute to ETL modernization and migration from traditional platforms to modern cloud-based data platforms.

Skills: "pyspark,databricks,sql,informatica powercenter
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