Job Summary

Drive the development of scalable data engineering and analytics solutions using Microsoft Fabric, Azure Synapse, Azure Data Factory, and Power BI. The role focuses on building reliable data pipelines, transforming and integrating data, developing analytical datasets, and enabling business reporting and analytics. The ideal candidate will have strong hands-on experience across up-to-date Azure data platforms and the ability to work closely with BI, data science, and business teams.

Roles and Responsibilities

- Data Engineering Pipelines: Design, develop, and maintain scalable ETL/ELT pipelines using Azure Data Factory (ADF) for data ingestion, transformation, cleansing, validation, and integration.
- Fabric Synapse Development: Develop and optimize notebook-based data engineering solutions using Microsoft Fabric and/or Azure Synapse, leveraging PySpark, Python, and SQL.
- Data Modeling: Work with structured and semi-structured data to build reliable analytical datasets and data models supporting reporting and business analytics.
- Power BI Analytics: Develop and optimize Power BI datasets, DAX measures, and calculated columns to support business reporting and analytical requirements.
- Performance Optimization: Optimize SQL queries, notebooks, pipelines, and data models to improve processing performance, scalability, and reliability.
- Data Quality Operations: Implement data quality checks, monitoring, error handling, troubleshooting, and operational processes to ensure reliable data delivery.




- Cross-Functional Collaboration: Partner with BI developers, data analysts, data scientists, and business stakeholders to understand requirements and deliver end-to-end data solutions.
- Modernization Delivery: Contribute to Azure Synapse and Microsoft Fabric migration/modernization initiatives, code reviews, technical discussions, documentation, and continuous improvement.

Required Skills

- Microsoft Fabric, Azure Synapse Analytics, Azure Data Factory (ADF), PySpark, Python, SQL, Power BI, DAX, ETL/ELT, Data Warehousing, Dimensional Modeling, and Data Integration.
- 5+ years of hands-on experience in Data Engineering or a related role.
- Strong experience developing Fabric/Synapse notebooks using PySpark, Python, and/or SQL.
- Hands-on expertise in ADF pipeline development, data ingestion, transformation, orchestration, and integration.
- Strong knowledge of Power BI and DAX, including developing and optimizing measures and calculated columns.
- Strong SQL skills with experience working with relational databases and data warehouses.
- Experience troubleshooting data pipeline failures, data quality issues, and performance bottlenecks.
- Strong analytical, problem-solving, communication, and stakeholder management skills.

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.

📌 Senior Analyst - Data Engineering (Madurai)
🏢 Latentview
📍 Madurai