Azure Data Engineer

Job Description:

At Exaze, we constantly seek exciting talent to join an organization that believes in nurturing dreamers, innovators, and doers willing to expand their horizons in the software industry. Our cultural foundation is our competitive advantage. We diligently seek out team members with a penchant for unconventional thinking and place them in environments conducive to their growth. We embrace a flat organizational structure while prioritizing internal mobility. If you possess an entrepreneurial mindset and a keen enthusiasm for learning and collaboration, this opportunity could propel your career to new heights

We are seeking a highly skilled Data Engineer to engineer and deliver Finance (Capital &Tax) domain-aligned data products within a centrally governed Microsoft Data Platform.

Key responsibility would be to build and maintain current ADF, Databricks and Azure Analysis Services cubes. Along with building new data products in Fabric within established standards, CI/CD templates, and defined data contracts, the Data Engineer will modernize SQL-driven legacy workloads and re-engineer them into scalable Spark-based Lakehouse datasets and semantic models.

Data products are treated as managed assets — version-controlled, tested, monitored, and continuously improved to meet defined quality and performance expectations.

Candidature Requirements:

- An Engineering graduate or Postgraduate from a recognized College / University.

- Strong aptitude, logical reasoning, and analytical thinking skills

- Excellent written and verbal communication skills

- Keen attention to detail, strong problem-solving skills

- Ability to work collaboratively in cross-functional teams using agile methodologies

- A values-driven individual who can think abstractly and take ownership of their work.

The role will include:

Lakehouse Engineering in Microsoft Fabric and Databricks

- Build and maintain bronze, silver, and gold layers in Microsoft Fabric and Databricks.

- Develop ingestion and transformation pipelines using:

Notebooks & Spark (PySpark preferred)

- Implement incremental loading and change data capture patterns from on-prem SQL to Fabric or Databricks.

- Optimize Delta tables for performance and cost efficiency.

- Ensure datasets align with defined data contracts and platform standards.

Data Product Ownership

- Engineer data products that are reliable, discoverable, and consumption ready.

- Apply testing and validation to ensure data quality and integrity.

- Monitor pipeline health and performance using platform-defined observability standards.

- Contribute to continuous improvement of data products based on usage and feedback.

- Collaborate closely with business stakeholders, analysts, and the central Data Platform team.

Experience, skill and capability

- 6+ years of hands-on experience in data engineering within SQL-heavy or enterprise data environments.

- Strong expertise in Microsoft SQL Server and advanced T-SQL development, including query optimization and performance tuning.

- Practical experience working with Microsoft Fabric and Lakehouse architecture principles.

- Hands-on experience with Spark (PySpark preferred) for distributed data transformation, Python notebooks.

- Solid understanding of dimensional modeling, including star schema and Kimball-based methodologies.

- Experience in Azure Data Factory, Databricks, AAS Cubes, MS Fabric, ADLS Gen2 , Purview

- Experience designing and optimizing semantic models for enterprise analytics platforms such as Power BI.

- Experience implementing incremental loading and change data  capture (CDC) patterns in hybrid environments.

- Experience building production-grade data pipelines with testing, monitoring, and CI/CD integration.

- Strong understanding of data governance principles, data contracts, and structured engineering standards.

- Experience working in enterprise-scale or regulated environments with disciplined delivery practices.

- Any financial services / banking / capital market experience

Required Qualifications

- Bachelor’s degree in computer science or related field from an accredited university and/or equivalent work experience

- Microsoft certifications (Azure Data Engineer, Fabric).

- Experience in distributed data processing environments.

- Experience in enterprise-scale or regulated environments.

- Exposure to AI/ML data preparation workflows.

Experience : 6+ Years

Job Location: Mumbai

Open Position: 1