5–8 yrsBengaluruOn-siteDirect career pageEst. 12–22 LPA
Posted 1d ago
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, optimize, and maintain end-to-end data pipelines and ETL processes using Microsoft Azure services, including Azure Data Factory, Synapse, Databricks, and Microsoft Fabric.
- Manage data storage solutions and organize pipeline outputs using Azure Data Lake Storage Gen2 and Azure Blob Storage with focus on data quality, integrity, and scalable performance.
- Oversee CI/CD pipelines for deployment and maintenance of data solutions, collaborate with cross-functional teams to meet data requirements, and troubleshoot pipeline issues efficiently.
Minimum Requirements
- Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience).
- 5-8 years of total experience with at least 3 years in data engineering or similar roles handling ETL and data processes.
- Strong hands-on experience with Microsoft Azure services including Azure Data Factory, Azure Databricks, Azure Synapse, Azure Blob Storage, and Azure Data Lake Storage Gen2.
- Proficiency in SQL DML for querying relational databases and practical experience with Apache Spark, plus knowledge of software engineering principles including CI/CD and version control.
Ideal Candidate Profile
- Experienced in advanced Spark implementations with strong programming skills in Python, Scala, or Java, and deep expertise in Azure Databricks.
- Capable of independently managing complex ETL/ELT pipelines across varied data sources and formats with a focus on reliable and scalable solutions.
- Familiar with DevOps practices including Azure DevOps pipelines, Git workflows, and has exposure to stakeholder management for delivering business-aligned data solutions.