Miracle Software Systems - Azure Data Engineer - ETL/Microsoft Fabric

Position Summary :

Key Responsibilities :

- Design and implement data pipelines in Microsoft Fabric to ingest, validate, and transform historical data (Invoices, Payments, POs, Shipments, GL, etc.) into Bronze, Silver, and Gold layers.

- Build and maintain semantic models aligned with Power BI and reporting requirements.

- Develop automated ETL/ELT processes ensuring daily/periodic data refresh and synchronization across multiple domains.

- Implement data quality and validation frameworks record counts, control totals, exception handling, and reconciliation.

- Configure and maintain data lineage, audit trails, and metadata for transparency and compliance (SOX, GxP, HIPAA).

- Set up automated alerting and monitoring systems for data quality, pipeline performance, and failure management.

- Collaborate closely with business SMEs, BI teams, and auditors to clarify requirements and ensure model accuracy.

- Participate in code reviews, testing, and deployment to ensure reliability, scalability, and performance.

- Document data flows, business rules, and pipeline logic in the knowledge repository.

Required Skills and Experience :

- 5+ years of experience in Data Engineering, with at least 2 years on Azure ecosystem (Synapse, Data Factory, Microsoft Fabric).

- Strong expertise in SQL, DAX, and Power Query (M).

- Hands-on experience with Data Lakehouse architectures and Delta/Parquet formats.

- Proficiency in building Fabric Data Pipelines, Lakehouse, and Semantic Models.

- Experience in data governance and security frameworks including RBAC, encryption, and compliance standards.

- Knowledge of data modeling principles (Star/Snowflake) and performance optimization for large datasets.

- Familiarity with Power BI data modeling and integration best practices.

- Strong problem-solving, communication, and documentation skills.

Preferred Qualifications :

- Microsoft Certified : Fabric Data Engineer Associate or Azure Data Engineer Associate.

- Exposure to financial, procurement, and logistics datasets.

- Experience with DevOps for Fabric or Synapse, including CI/CD automation.

- Understanding of AI-readiness principles and analytics enablement.