Lead Data Architect, Fabric

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🔥 1 minute ago

🇮🇳 India – Remote

💵 ₹2M - ₹6M / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

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Weekday

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2002

👗 Fashion

🛒 Retail

🛍️ eCommerce

Fashion • Retail • eCommerce

Weekday is your everyday paradox wrapped in denim—unapologetic, unpredictable, and always evolving. Discover our full range of men’s and women’s fashion, from statement Weekday jeans and perfectly imperfect suiting to comfort-first underwear and bold pop culture-inspired graphic prints. Build your wardrobe with Astro jeans and chunky scuba pieces, ideal for creating relaxed yet modern outfits. Explore essential mini and maxi skirts, oversized shirts, short sleeve tops, and lightweight jackets—all available in muted tones and bold seasonal hues. Whether you're styling half-tucked tees or layered looks, Weekday offers statement pieces and versatile basics to fit your mood, your moment, and your everyday, embracing the many true expressions of youth.

📋 Description

• Lead the end-to-end architecture, design, and implementation of enterprise Microsoft Fabric solutions • Define technical architecture, engineering standards, reusable frameworks, and best practices • Own OneLake structure, workspace strategy, capacity planning, and domain segregation • Establish medallion architecture across Bronze, Silver, and Gold data layers • Provide technical leadership to data engineers and developers • Design and implement enterprise data platforms using Microsoft Fabric, including OneLake, Lakehouse, Data Warehouse, Data Factory, Data Engineering, Real-Time Intelligence, and Power BI • Design and develop ETL/ELT pipelines using Microsoft Fabric Data Factory and Spark Notebooks • Integrate structured, semi-structured, and unstructured data from cloud and on-premises systems • Design dimensional data models, Lakehouse architectures, enterprise data warehouses, semantic models, and datasets • Define and implement DevOps, Git integration, deployment pipelines, CI/CD, automated testing, release management, rollback, infrastructure-as-code, and source control practices • Architect and enforce security, access controls, governance, compliance, workspace roles, OneLake policies, sensitivity labels, and row-level security • Optimise Spark workloads, SQL Warehouse performance, OneLake storage, partitioning, indexing, caching, and resource utilisation • Lead migrations from Azure Synapse Analytics, Azure Data Factory, on-premises SSIS/SQL Server, and other cloud data warehouses to Microsoft Fabric • Enable AI, Machine Learning, and Copilot capabilities within Microsoft Fabric • Lead production deployments and post-deployment support; monitor platform health, troubleshoot incidents, and ensure SLA compliance • Establish disaster recovery, backup, and business continuity strategies • Collaborate with enterprise architects, product owners, business stakeholders, and cross-functional teams • Mentor data engineers and developers; conduct code and design reviews and knowledge-sharing sessions • Drive continuous improvement and engineering excellence

🎯 Requirements

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related discipline • 10+ years of experience in Data Engineering, Data Warehousing, or Cloud Data Platform development • Minimum 8+ years of overall professional experience is mandatory • 4+ years of hands-on experience with Microsoft Azure Data Platform technologies • At least 2 years of hands-on experience implementing Microsoft Fabric in enterprise environments • Strong expertise in SQL, Python, PySpark, and Apache Spark optimisation • Hands-on experience with Microsoft Fabric components, including OneLake, Lakehouse, Data Warehouse, Data Factory, Power BI, and Real-Time Intelligence • Experience with Azure Data Lake Storage (ADLS), Azure DevOps, GitHub, and CI/CD pipelines • Strong understanding of dimensional data modelling, ETL/ELT architecture, and data governance • Proven experience designing scalable data platforms and leading enterprise-level data engineering initiatives • Must-have skills: Microsoft Fabric, Databricks, PySpark • Good-to-have skills: SQL, Azure Data Factory, ETL/ELT • Preferred qualifications: Microsoft certifications such as DP-600, DP-203, or Azure Solutions Architect Expert; Power BI semantic model optimisation and DirectLake mode; data mesh and domain-driven data architecture; Databricks, Azure Synapse Analytics, Azure AI Services, or Microsoft Purview; Agile/Scrum delivery methodologies; strong communication, stakeholder management, problem-solving, and technical leadership skills

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