{"id":1247455,"url":"https://alion.io/job/algoworks-senior-microsoft-fabric-performance-scalability-specialist","title":"Senior Microsoft Fabric Performance & Scalability Specialist","company":{"id":2091826,"name":"Algoworks","domain":"algoworks.com","url":"https://alion.io/company/algoworks-com","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Keka","truth_index":null},"role":"Field & Service","role_family":"Field & Service","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Noida, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":3000000,"max":3500000,"currency":"INR","period":"year","gross":null,"usd_annual":36131},"salary_estimate":null,"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"ETL/ELT","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"SQL","optional":false},{"name":"Azure Data Factory","optional":true},{"name":"Databricks","optional":true},{"name":"Delta Lake","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-09-24T04:49:26Z","employer_posted_date":"2026-09-24","last_verified_at":"2026-10-21T06:37:22Z","board_verified":true,"closed_at":null,"days_open":27,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":27},"description":"Role: Senior Microsoft Fabric Performance & Scalability Specialist\nLocation: India, Remote\nExperience: 10+ Years\nAlgoworks\nwww.algoworks.com\nAbout the company\nAlgoworks is an award-winning artificial intelligence, engineering services and experience transformation firm with offices across the United States, Europe, South America and India. We bring together a global team of engineers, architects, designers, researchers and operators united by rigor, accountability and a commitment to delivering measurable results.\nFor over 20 years, Algoworks has partnered with Fortune 500 organizations across the Americas, Europe and Asia to define, build and run technology that drives meaningful business outcomes. Our work combines human-centered design, engineering excellence and AI-powered capabilities to solve complex challenges with clarity and precision. Innovation, particularly in the responsible application of AI, is embedded in how teams approach problem-solving and continuous improvement.\nAt Algoworks, growth is continuous and closely tied to impact. Teams collaborate across geographies and disciplines, strengthening outcomes through shared insight and collective expertise. The culture values transparency, open dialogue and an environment where every voice is heard and contribution is recognized.\nThrough collaboration, accountability and a focus on results, Algoworks operates at the intersection of technology and people, building not only advanced systems but strong global teams that elevate performance and create lasting impact.\nFollow the video below to know about us! Clipchamp\nRole overview\nWe 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.\nThe 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.\nStrong hands-on experience with Microsoft Fabric, Fabric Data Warehouse, Lakehouse, PySpark/Python, SQL performance tuning, and Medallion Architecture (Bronze/Silver/Gold) is mandatory.\nKey responsibilities:\n1.Fabric Performance & Scalability\nOptimize Microsoft Fabric performance, scalability, concurrency, and capacity utilization across Fabric Data Warehouse, Lakehouse, OneLake, Shortcuts, Pipelines, and Notebooks.\nDesign and enhance the platform to efficiently support migration and ongoing processing for 1,500+ tenants/clients.\nDevelop scalable processing strategies for high-volume and low-volume tenants while meeting data-load and reporting SLAs.\nAnalyze Fabric capacity/CU utilization, throttling, concurrency, Query Insights, and workload performance.\nImplement optimization recommendations to improve performance, scalability, and resource utilization.\nOptimize tenant grouping, batching, parallel processing, concurrency control, workload prioritization, watermark/batch processing, retries, and failure recovery.\nOptimize Fabric Data Warehouse SQL queries, data loads, joins, table structures, and CLUSTER BY strategies.\nConduct performance, scalability, concurrency, stress, and load testing and establish measurable performance benchmarks.\n2.Fabric Development & Data Processing\nDevelop and enhance Fabric notebooks using PySpark, Python, and SQL for scalable full and incremental processing.\nBuild reusable and scalable processing frameworks for multi-tenant workloads.\nDevelop and optimize Fabric pipelines and data-processing workflows.\nImplement reliable failure recovery, retry, batching, and incremental-processing mechanisms.\nEnsure development follows scalable, maintainable, and production-ready engineering practices.\n3.New Data Source Development & Onboarding\nWork closely with the ETL/Data Engineering team to onboard new data sources and new sets of tables into Microsoft Fabric.\nAnalyze new source schemas, tables, relationships, data volumes, dependencies, primary keys, and incremental-load requirements.\nPerform required development, code changes, configuration, and testing in Microsoft Fabric to support newly introduced data sources and tables.\nDevelop and enhance Fabric notebooks, pipelines, SQL code, metadata/control frameworks, Lakehouse objects, and Fabric Data Warehouse tables required for new data sources.\nConfigure and test full and incremental data-loading processes for newly onboarded tables.\nPerform unit, integration, data-validation, and performance testing before production deployment.\nCoordinate with ETL teams to validate source-to-target mappings, transformation logic, dependencies, and data completeness.\nIntegrate new data sources into the established Bronze → Silver → Gold → Lakehouse/Fabric Data Warehouse architecture.\nDevelop reusable and metadata-driven patterns to reduce development effort when onboarding future data sources and tables.\n4.Client Onboarding & Production Support\nWork directly with clients and internal teams during onboarding, migration, production cutover, and post-production support.\nUnderstand client data volumes, processing requirements, dependencies, and SLA expectations.\nSupport client onboarding including full loads, incremental-load enablement, data validation, performance validation, and production cutover.\nInvestigate and resolve client-reported data, performance, data-load, and reporting issues.\nPerform end-to-end root-cause analysis across source systems, Medallion layers, Fabric notebooks, pipelines, Lakehouse, Data Warehouse, and reporting workloads.\nTroubleshoot missing or duplicate data, failed or delayed loads, incremental-processing issues, performance degradation, and SLA violations.\nImplement permanent fixes and enhance shared frameworks to prevent recurring issues across tenants.\n5.Production Performance & SLA Management\nMonitor production workloads and ensure data-load and reporting SLAs are consistently achieved.\nIdentify performance bottlenecks, capacity constraints, concurrency issues, and processing failures.\nPrioritize production issues based on business impact and SLA requirements.\nCoordinate with ETL, Data Engineering, reporting, and client-facing teams to resolve complex production issues.\nDocument root-cause analysis, corrective actions, and preventive measures.\nDrive continuous improvements to platform reliability, performance, and scalability.\nRequired technical skills and competencies:\n10+ years of experience in Data Engineering, Data Warehousing, ETL/ELT, or enterprise data platforms.\nStrong recent hands-on Microsoft Fabric production experience.\nProven experience in Microsoft Fabric performance optimization and scalability.\nStrong hands-on experience with Fabric Data Warehouse, Lakehouse, OneLake, Pipelines, and Notebooks.\nAdvanced PySpark, Python, and SQL development and performance-tuning skills.\nStrong production experience with Medallion Architecture (Bronze/Silver/Gold) - mandatory.\nExperience developing and optimizing large-scale full and incremental data-loading frameworks.\nExperience handling high-volume, concurrent, and multi-tenant workloads.\nStrong understanding of Fabric capacity, CU utilization, concurrency, throttling, and workload management.\nHands-on experience with new data-source/table onboarding, development, testing, and production deployment.\nExperience working collaboratively with ETL/Data Engineering teams to implement source-to-target data pipelines.\nExperience working directly with clients during onboarding, migration, and production issue resolution.\nStrong troubleshooting, root-cause analysis, communication, and problem-solving skills.\nMust have skills:\nMicrosoft Fabric.\nFabric Data Warehouse.\nMicrosoft Fabric Lakehouse.\nOneLake.\nFabric Pipelines.\nFabric Notebooks.\nPySpark.\nPython.\nAdvanced SQL.\nSQL Performance Tuning.\nMedallion Architecture - Bronze/Silver/Gold.\nFull and Incremental Data Processing.\nMulti-Tenant Data Processing.\nFabric Capacity and CU Optimization.\nConcurrency and Workload Management.\nData Source and Table Onboarding.\nProduction Support and Troubleshooting.\nSLA Management.\nGood to have skills:\nExperience supporting platforms with 1,000+ tenants/clients or comparable enterprise-scale workloads.\nFabric F-SKU capacity optimization and workload management.\nADLS Gen2.\nAzure Data Factory.\nDatabricks.\nDelta Lake.\nOneLake Shortcuts.\nMetadata-driven ETL/ELT frameworks.\nLarge-scale data migration.\nLoad and concurrency testing.\nHigh-concurrency reporting workloads.\nDesired attributes:\nStrong hands-on development and performance optimization mindset.\nAbility to take a new data source or set of tables from analysis through Fabric development, testing, deployment, and production support.\nStrong production troubleshooting and root-cause analysis capabilities.\nAbility to work effectively with ETL, Data Engineering, reporting, and client-facing teams.\nStrong understanding of enterprise-scale and multi-tenant data processing.\nExcellent communication and stakeholder management skills.\nStrong ownership of production stability, performance, and SLA adherence.\nAbility to work effectively in a high-volume, fast-paced production environment.\nStrong analytical and problem-solving capabilities.\nProactive approach to performance optimization and continuous improvement.\nInterview Process\n2-3 rounds of 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