The role involves close collaboration with Data Analysts, Architects, Engineering teams, and Business Stakeholders to deliver high-quality, robust, and performance-driven data solutions.

Key Responsibilities:
Work closely with business stakeholders and Data Analysts to understand business and data requirements.
Perform ad hoc data analysis and transformation using Databricks, MS Fabric, and Azure Synapse Analytics.
Build metadata-driven data ingestion frameworks using Azure Data Factory, Databricks, MS Fabric, and Synapse.
Design, develop, and maintain on-premises SQL Data Warehouse solutions.
Develop and maintain business-focused data products and Azure Analysis Services cubes.
Build scalable ETL and ELT pipelines for enterprise data processing.
Collaborate with Architecture and Engineering teams to ensure best practices across code, infrastructure, and deployment.
Develop Infrastructure-as-Code deployment pipelines and CI/CD automation processes.
Contribute to engineering standards, documentation, governance, and knowledge-sharing initiatives.




Support contemporary data architecture implementations including Lakehouse and Medallion architecture frameworks.

Required Skills & Technologies:
Strong experience in Azure Data Factory, Databricks, MS Fabric, Azure Synapse Analytics, and ADLS Gen2.
Expertise in Python, PySpark, T-SQL, SQL Server, SSIS, SSAS, and SSRS.
Robust knowledge of ETL/ELT development and enterprise data pipeline architecture.
Hands-on experience with Data Warehousing concepts including Star Schema and Snowflake Schema.
Experience building scalable and performant data platforms in Azure environments.
Knowledge of CI/CD pipelines, source control, and Infrastructure-as-Code deployments.
Familiarity with up-to-date data engineering practices including Lakehouse and Medallion architecture.
Strong analytical, troubleshooting, and problem-solving capabilities.
Excellent communication and stakeholder management skills.
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📌 Data Engineer Mumbai (India)
🏢 Talent Aquisition Consultant
📍 India