- End-to-end design and operation of enterprise-scale data pipelines and infrastructure using Azure Databricks, Azure Service Fabric, and related Azure services.

- You will ensure data availability, reliability, and quality across HR, Procurement, and Finance functions while applying software engineering best practices such as modular design, TDD, and CI/CD automation.

- You will collaborate with business stakeholders, architects, ML/AI engineers, Fabric service teams, and Power BI developers to align delivery with business outcomes, operating within an agile team structure.

Key Responsibilities :

- Data Pipeline & Microservices Engineering : Design and operate scalable, high-performance data pipelines and service-oriented components using Azure Databricks, Azure Service Fabric, and other Azure ecosystem services.

- Code as Assets : Develop all artifacts as version-controlled code (Git) with CI/CD automation.

Data Reliability & Quality : Ensure availability, integrity, and quality of data supporting analytics in HR, Procurement, and Finance.

- Analytical Assets : Build data products and assets leveraging software engineering best practices.

- Engineering Practices : Apply modular design, TDD, reusable code patterns, and performance optimization.

- Fabric Service Monitoring & Management : Deploy, monitor, and maintain microservices on

Azure Service Fabric, ensuring high availability, resiliency, and scalability.

- Collaboration : Work closely with architects, ML/AI engineers, functional IT, Power BI developers, Fabric service teams, and business stakeholders to align solutions with requirements.

- Agile Contribution : Actively participate in sprint planning, retrospectives, and demos within an enterprise agile product team.

- Monitoring & Optimization : Monitor and improve data & service infrastructure performance, proactively identifying bottlenecks, failure points, and optimization opportunities.

Required Skills & Qualifications :

- Strong experience with Azure Databricks, Azure Service Fabric, and the broader Azure Data - ecosystem (ADF, Synapse, Data Lake, Event Hub).

- Proficiency in Python / Scala / SQL for data engineering.

- Hands-on experience in CI/CD automation, Git version control, and test-driven development (TDD).

- Deep understanding of data modeling, ETL/ELT pipelines, modular design patterns.

- Experience in building, deploying, and maintaining microservices in Azure Service Fabric (or equivalent orchestrated service mesh / containerized services).

- Ability to build analytical data products using engineering-first principles.

- Experience working in agile, enterprise-scale environments.

- Strong problem-solving and debugging skills

Preferred Qualifications :

- Exposure to AI/ML pipelines integration in data workflows.

- Experience with Power BI or equivalent BI platforms.

- Knowledge of DevOps practices in a cloud-first environment.

- Microsoft Azure Data Engineer Associate certification (or equivalent).

- Familiarity with containerization technologies (e.g. Docker), orchestration (e.g. Kubernetes), in addition to Service Fabric.