Databricks Engineer

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.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.