Job Summary

Role: Senior Microsoft Fabric Performance Scalability Specialist

Location: India, Remote

Experience: 10+ Years

Role overview

We are seeking a hands-on Senior Microsoft Fabric Performance Scalability Specialist with 10+ years of Data Engineering/Data Warehousing experience to optimize, scale, develop, and support an enterprise Microsoft Fabric platform supporting 1,500+ clients/tenants.

The role will focus on Fabric performance optimization, multi-tenant scalability, Fabric development, new data-source onboarding, client onboarding and support, production issue resolution, and SLA management.

Solid hands-on experience with Microsoft Fabric, Fabric Data Warehouse, Lakehouse, PySpark/Python, SQL performance tuning, and Medallion Architecture (Bronze/Silver/Gold) is mandatory.

Key responsibilities

1. Fabric Performance Scalability

- Optimize Microsoft Fabric performance, scalability, concurrency, and capacity utilization across Fabric Data Warehouse, Lakehouse, OneLake, Shortcuts, Pipelines, and Notebooks.
- Design and enhance the platform to efficiently support migration and ongoing processing for 1,500+ tenants/clients.
- Develop scalable processing strategies for high-volume and low-volume tenants while meeting data-load and reporting SLAs.
- Analyze Fabric capacity/CU utilization, throttling, concurrency, Query Insights, and workload performance.
- Implement optimization recommendations to improve performance, scalability, and resource utilization.
- Optimize tenant grouping, batching, parallel processing, concurrency control, workload prioritization, watermark/batch processing, retries, and failure recovery.
- Optimize Fabric Data Warehouse SQL queries, data loads, joins, table structures, and CLUSTER BY strategies.
- Conduct performance, scalability, concurrency, stress, and load testing and establish measurable performance benchmarks.

2. Fabric Development Data Processing

- Develop and enhance Fabric notebooks using PySpark, Python, and SQL for scalable full and incremental processing.




- Build reusable and scalable processing frameworks for multi-tenant workloads.
- Develop and optimize Fabric pipelines and data-processing workflows.
- Implement reliable failure recovery, retry, batching, and incremental-processing mechanisms.
- Ensure development follows scalable, maintainable, and production-ready engineering practices.

3. New Data Source Development Onboarding

- Work closely with the ETL/Data Engineering team to onboard new data sources and new sets of tables into Microsoft Fabric.
- Analyze new source schemas, tables, relationships, data volumes, dependencies, primary keys, and incremental-load requirements.
- Perform required development, code changes, configuration, and testing in Microsoft Fabric to support newly introduced data sources and tables.
- Develop and enhance Fabric notebooks, pipelines, SQL code, metadata/control frameworks, Lakehouse objects, and Fabric Data Warehouse tables required for new data sources.
- Configure and test full and incremental data-loading processes for newly onboarded tables.
- Perform unit, integration, data-validation, and performance testing before production deployment.
- Coordinate with ETL teams to validate source-to-target mappings, transformation logic, dependencies, and data completeness.
- Integrate new data sources into the established Bronze Silver Gold Lakehouse/Fabric Data Warehouse architecture.
- Develop reusable and metadata-driven patterns to reduce development effort when onboarding future data sources and tables.

4. Client Onboarding Production Support

- Work directly with clients and internal teams during onboarding, migration, production cutover, and post-production support.
- Understand client data volumes, processing requirements,



dependencies, and SLA expectations.
- Support client onboarding including full loads, incremental-load enablement, data validation, performance validation, and production cutover.
- Investigate and resolve client-reported data, performance, data-load, and reporting issues.
- Perform end-to-end root-cause analysis across source systems, Medallion layers, Fabric notebooks, pipelines, Lakehouse, Data Warehouse, and reporting workloads.
- Troubleshoot missing or duplicate data, failed or delayed loads, incremental-processing issues, performance degradation, and SLA violations.
- Implement permanent fixes and enhance shared frameworks to prevent recurring issues across tenants.

5. Production Performance SLA Management

- Monitor production workloads and ensure data-load and reporting SLAs are consistently achieved.
- Identify performance bottlenecks, capacity constraints, concurrency issues, and processing failures.
- Prioritize production issues based on business impact and SLA requirements.
- Coordinate with ETL, Data Engineering, reporting, and client-facing teams to resolve complex production issues.
- Document root-cause analysis, corrective actions, and preventive measures.
- Drive continuous improvements to platform reliability, performance, and scalability.

Required technical skills and competencies

- 10+ years of experience in Data Engineering, Data Warehousing, ETL/ELT, or enterprise data platforms.
- Robust recent hands-on Microsoft Fabric production experience.
- Proven experience in Microsoft Fabric performance optimization and scalability.
- Strong hands-on experience with Fabric Data Warehouse, Lakehouse, OneLake, Pipelines, and Notebooks.
- Advanced PySpark, Python, and SQL development and performance

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.

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