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Weekday AI

Proactive software engineer recruitment via referrals

Lead Data Architect - Fabric

Data EngineeringPosted on Nov 13
Full-timeRemote in India₹2M - ₹6M

About the Job

Requirements

  • A Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related discipline is required.
  • At least 8 years of overall professional experience is mandatory; 10 or more years of experience in data engineering, data warehousing, or cloud data platform development is specified.
  • At least 4 years of hands-on experience with Microsoft Azure Data Platform technologies is required.
  • At least 2 years of hands-on experience implementing Microsoft Fabric in enterprise environments is required.
  • Strong expertise in SQL, Python, PySpark, and Apache Spark optimisation is required.
  • Hands-on experience with Microsoft Fabric components, including OneLake, Lakehouse, Data Warehouse, Data Factory, Power BI, and Real-Time Intelligence, is required.
  • Experience with Azure Data Lake Storage, Azure DevOps, GitHub, and CI/CD pipelines is required.
  • Strong understanding of dimensional data modelling, ETL/ELT architecture, and data governance is required.
  • Proven experience designing scalable data platforms and leading enterprise-level data engineering initiatives is required.
  • Microsoft Fabric, Databricks, and PySpark are listed as must-have skills.

Responsibilities

  • Lead the end-to-end architecture, design, and implementation of enterprise Microsoft Fabric solutions.
  • Define technical architecture, engineering standards, reusable frameworks, and best practices for platform adoption.
  • Own the architecture of the unified data ecosystem, including OneLake structure, workspace strategy, capacity planning, and domain segregation.
  • Establish medallion architecture patterns across Bronze, Silver, and Gold data layers.
  • Provide technical leadership to data engineers and developers, ensuring quality, scalability, and consistency.
  • Review solution designs, code, and deployment strategies to ensure alignment with architectural standards.
  • Design and implement enterprise data platforms using Microsoft Fabric components, including OneLake, Lakehouse, Data Warehouse, Data Factory, Data Engineering, Real-Time Intelligence, and Power BI.
  • Architect scalable, cloud-native data solutions supporting analytics, AI, and business intelligence requirements.
  • Define workspace and capacity strategies, domain-level segregation, and platform design standards, and leverage Fabric capabilities to establish a unified, scalable, and secure enterprise data environment.
  • Design and develop robust ETL/ELT pipelines using Microsoft Fabric Data Factory and Spark Notebooks.
  • Integrate structured, semi-structured, and unstructured data from cloud-based and on-premises systems.
  • Implement data ingestion, transformation, cleansing, validation, and orchestration processes, and optimise ingestion strategies for reliability, scalability, and performance.
  • Use SQL, Python, PySpark, and Apache Spark to build and optimise data engineering solutions.
  • Design dimensional data models, Lakehouse architectures, and enterprise data warehouses.
  • Develop semantic models and datasets to support Power BI reporting and self-service analytics.
  • Translate business and analytical requirements into scalable data architecture and engineering solutions, and establish data modelling standards and reusable patterns across enterprise workloads.
  • Define and implement DevOps practices for Microsoft Fabric, including Git integration, deployment pipelines, and environment promotion across Development, QA, UAT, and Production.
  • Build and maintain CI/CD pipelines using Azure DevOps or GitHub Actions.
  • Automate deployment of Fabric artefacts, including Lakehouses, Warehouses, Notebooks, Pipelines, and Semantic Models.
  • Implement automated testing, validation, release management, and rollback strategies; establish infrastructure-as-code and source control practices for Fabric workloads.
  • Architect and enforce enterprise security and access controls across Microsoft Fabric.
  • Implement workspace roles, OneLake data access policies, sensitivity labels, and row-level security.
  • Work with Microsoft Entra ID, Role-Based Access Control, and Microsoft Purview to establish governance frameworks.
  • Ensure compliance with enterprise security, privacy, and regulatory requirements, and establish consistent data governance and access management practices.
  • Optimise Spark workloads, SQL Warehouse performance, and OneLake storage utilisation.
  • Implement partitioning, indexing, caching, and workload optimisation strategies; monitor platform performance, identify bottlenecks, and improve system efficiency.
  • Ensure scalability, reliability, and efficient resource utilisation across data workloads.
  • Lead migration initiatives from legacy data platforms, including Azure Synapse Analytics, Azure Data Factory, on-premises SSIS/SQL Server, and other cloud data warehouses, to Microsoft Fabric.
  • Define migration strategies, architecture patterns, and implementation roadmaps; ensure smooth integration, data consistency, and minimal disruption during platform transitions.
  • Enable AI, Machine Learning, and Copilot capabilities within Microsoft Fabric.
  • Support data science workloads using Spark, notebooks, and machine learning models; collaborate with AI teams to operationalise predictive analytics and intelligent data solutions.
  • Leverage AI capabilities to improve engineering productivity and data platform efficiency.
  • Lead production deployments and post-deployment support activities.
  • 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.
  • Participate in architecture review boards and technical governance meetings.
  • Communicate technical solutions, implementation plans, and project status to senior leadership.
  • Mentor data engineers and developers on Microsoft Fabric architecture and engineering best practices.
  • Conduct code reviews, design reviews, and technical knowledge-sharing sessions.
  • Drive continuous improvement initiatives and promote engineering excellence.

Desired Qualifications

  • Microsoft certifications such as DP-600 (Fabric Analytics Engineer), DP-203 (Azure Data Engineer), or Azure Solutions Architect Expert are preferred.
  • Experience with Power BI semantic model optimisation and DirectLake mode is preferred.
  • Familiarity with data mesh and domain-driven data architecture principles is preferred.
  • Experience with Databricks, Azure Synapse Analytics, Azure AI Services, or Microsoft Purview is preferred.
  • Knowledge of Agile/Scrum delivery methodologies is preferred.
  • SQL, Azure Data Factory, and ETL/ELT are listed as good-to-have skills.

About the Company

Weekday AI

Proactive software engineer recruitment via referrals

Weekday.works helps companies hire software engineers through proactive outreach and peer-recommended candidates. Its platform automates tracking, pipeline management, and provides weekly updates, while it actively identifies engineers via peer networks, reaches out, shortlists, checks references, and schedules interviews. Differentiators include peer-backed vetting instead of traditional job boards, proactive outreach, and a passive-income reference feature that monetizes referrals. The goal is to reduce the time and effort of hiring by connecting companies with pre-vetted engineers who are open to new opportunities through a network-driven approach.

Company size
201-500
Company stage
Seed
Total funding
$2.3M
Headquarters
Bengaluru, India
Founded
2021

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