Job Overview

We are looking for an experienced Databricks Engineer with a strong background in Informatica PowerCenter, ETL, Data Warehousing, Data Modeling, and up-to-date 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

📌 Databricks Engineer (Mumbai)
🏢 Zorba AI
📍 Mumbai