Senior Data Engineer – Microsoft Fabric & Data Integration - Pune/Chennai

Position Summary

We are seeking a highly skilled Senior Data Engineer to design, develop, optimize, and support modern enterprise data platforms and data integration solutions. This role is responsible for building scalable data pipelines, data warehouses, ETL/ELT frameworks, and analytics-ready data architectures utilizing Microsoft Fabric, Azure Data Factory, Fabric Data Factory, SQL Server, and associated technologies. The ideal candidate will possess deep expertise in SQL development, data warehousing methodologies, ETL/ELT best practices, and cloud-based data engineering. Our engineering organization has adopted Specification-Driven Development (SDD) as a core practice emphasizing clear requirements, technical specifications, automation, quality, and maintainability. We also view Artificial Intelligence and AI-assisted engineering as strategic investments in our future.

Key Responsibilities

Design, build, and maintain scalable, reliable, and secure data integration and analytics solutions.

Develop enterprise platforms utilizing Microsoft Fabric, Fabric Data Factory, Azure Data Factory, SQL Server, OneLake, Lakehouse, and Data Warehouse architectures.

Design and implement modern ETL and ELT frameworks supporting analytics, reporting, and operational use cases.

Develop ingestion, transformation, orchestration, monitoring, data quality, and reconciliation processes.

Participate in Specification-Driven Development practices and create technical specifications and design documentation.

Design solutions supporting AI, machine learning, generative AI, and advanced analytics initiatives.

Support CI/CD, monitoring, production operations, root-cause analysis, and continuous improvement.

Required Qualifications

Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or related field, or equivalent practical experience.

7 + years of experience in data engineering, data warehousing, ETL/ELT development, or related disciplines.

Experience designing and implementing enterprise-scale data warehouse and analytics platforms.

Experience with Azure cloud-based data engineering solutions and Agile delivery practices.

Required Technical Skills

Microsoft Fabric (Lakehouse, Data Warehouse, Data Factory, OneLake)

Azure Data Factory and Fabric Data Factory

SQL Server and advanced T-SQL

ETL and ELT architecture and development

Dimensional modeling and data warehouse design

Data orchestration and automation

Data governance and data quality

Git and Azure DevOps

Preferred Qualifications

Pentaho Data Integration (PDI/Kettle)

SQL Server Integration Services (SSIS)

Azure Synapse Analytics

Azure Data Lake Storage

Spark and PySpark

Power BI

Data Vault methodology

Infrastructure as Code

CI/CD for data platforms

Experience with SDD methodologies

Experience supporting AI, machine learning, generative AI, or advanced analytics

Legacy Platform Experience (Beneficial)

Qlik Replicate

Qlik Compose

Legacy ETL migration and modernization programs

CDC and data replication architectures

Migration of legacy data solutions into Microsoft Fabric and Azure environments

Knowledge & Competencies

Kimball dimensional modeling

Fact and dimension design

Slowly Changing Dimensions (Types 1, 2, and 3)

Data quality and governance

CDC and incremental loading strategies

Metadata-driven processing

Performance optimization and scalability

Strong analytical, communication, and problem-solving skills

Success Criteria

Build scalable, secure, and reliable enterprise data pipelines and integration solutions.

Deliver optimized Microsoft Fabric warehouse and lakehouse solutions.

Establish and follow ETL/ELT best practices and engineering standards.

Improve data quality, reliability, and accessibility.

Enable analytics, reporting, AI, and data-driven decision making.

Deliver high-quality solutions through disciplined Specification-Driven Development practices.

Actively contribute to the organization's AI strategy through architecture, automation, and innovation.

Help establish modern engineering practices that improve productivity, quality, and maintainability.

Work on a team leading in the adoption of Microsoft Fabric and AI-enabled data engineering capabilities.

Our Interview Practices

To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you—not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.

Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.