Client: The client is a global asset management, investment management, and financial products company operating across the United States and in more than 40 countries.

Project overview: This project focuses on modernizing and scaling an enterprise data ecosystem using Microsoft Fabric. The platform supports analytics, reporting, investment, product, distribution, and operational functions while emphasizing governance, performance, security, and reusable architecture patterns across the organization.

- Position overview: We are looking for an experienced Fabric Architect to design and implement scalable enterprise data architectures using Microsoft Fabric. In this role, you will focus on Microsoft Fabric Lakehouse, OneLake, Data Warehouse, data engineering, and enterprise Power BI semantic models.
- You will define data modeling standards, medallion architecture, ingestion and transformation patterns, semantic layer design, governance, security, data quality, and performance optimization practices. This is a hands on architecture role that requires translating complex business and technical requirements into robust, reusable, and maintainable data solutions.
- You will partner with data engineering, analytics, infrastructure, security, and business teams while providing technical direction and establishing best practices for the enterprise data platform.
- This role requires full coverage with an EST work schedule.

Technology stack: Microsoft Fabric, OneLake, Fabric Lakehouse, Fabric Data Warehouse, Data Factory, Dataflows Gen2, Power BI, DAX, Power Query, Delta Lake, Parquet, SQL, Python, PySpark, Microsoft Entra ID, Git, CI/CD, Azure Data Lake Storage, Azure Data Factory, Azure Synapse Analytics, Azure Key Vault, Azure Monitor, Microsoft Purview
- Responsibilities: Design end to end enterprise data architectures using Microsoft Fabric, including OneLake, Lakehouse, Data Warehouse, data pipelines, notebooks, and Power BI semantic models.
- Define and implement medallion architecture using bronze, silver, and gold data layers.
- Establish architecture standards for data ingestion, transformation, storage, modeling, consumption, and lifecycle management.
- Design scalable Lakehouse and data warehouse solutions for structured, semi structured, and unstructured data.
- Define OneLake organization, workspace, domain, shortcut, naming, and data sharing standards.
- Design enterprise grade Power BI semantic models using dimensional modeling, star schemas, reusable dimensions, governed measures, DAX, calculation groups, and shared business definitions.
- Determine the appropriate use of Direct Lake, Import, DirectQuery,



and composite models based on performance, scale, freshness, security, and business requirements.
- Define batch, near real time, and event driven ingestion and transformation patterns.
- Guide the use of Fabric Data Factory, Dataflows Gen2, notebooks, Spark, SQL, APIs, and other integration mechanisms.
- Optimize Fabric capacities, Delta tables, SQL workloads, pipelines, notebooks, semantic models, and Power BI reports for performance, reliability, and cost efficiency.
- Define security patterns using Microsoft Entra ID, role based access control, workspace permissions, row level security, object level security, managed identities, and data classification.
- Establish data governance, lineage, metadata, retention, auditing, and regulatory compliance practices.
- Define data quality frameworks covering validation, reconciliation, completeness, accuracy, timeliness, exception handling, and issue monitoring.
- Develop reusable architecture patterns, templates, reference implementations, and technical standards.
- Translate business and non functional requirements into logical and physical data architectures.
- Conduct architecture reviews, design reviews, technical assessments, and proof of concept implementations.
- Establish source control, testing, CI/CD, release, deployment, and environment management practices for Fabric solutions.
- Troubleshoot complex production, performance, capacity, security, and data reliability issues.
- Maintain architecture diagrams, data flow documentation, design decisions, standards, and implementation roadmaps.
- Mentor data engineers, BI developers, and analytics teams while promoting adherence to architecture standards.
- Communicate technical decisions, risks, dependencies, and trade offs clearly to both technical and non technical stakeholders.
- 8+ years of experience in data architecture, data engineering, business intelligence, analytics architecture, or enterprise data platform delivery.
- Strong hands on experience designing and implementing production solutions using Microsoft Fabric.
- Deep understanding of OneLake, Fabric Lakehouse, Fabric Data Warehouse, Data Factory, notebooks, pipelines, semantic models, and Power BI.
- Strong experience with medallion architecture, data lake architecture,



Delta Lake, Parquet, and scalable data processing patterns.
- Strong expertise in dimensional modeling, star and snowflake schemas, slowly changing dimensions, shared dimensions, metrics, and enterprise semantic modeling.
- Strong experience developing Power BI semantic models, including DAX, Power Query, calculation groups, relationships, aggregations, incremental refresh, and performance optimization.
- Experience selecting and implementing Direct Lake, Import, DirectQuery, and composite storage modes.
- Advanced SQL skills and strong working knowledge of Python or PySpark.
- Experience integrating relational databases, files, APIs, cloud services, external data sources, and streaming or event based sources.
- Strong knowledge of data security, governance, lineage, classification, privacy, and access control principles.
- Experience designing data quality, reconciliation, observability, monitoring, and exception management frameworks.
- Solid understanding of Fabric capacity management, workload monitoring, query optimization, scalability, resilience, and cost management.
- Experience with Git based development, automated testing, CI/CD, deployment pipelines, and environment management practices.
- Ability to translate complex business requirements into transparent architectures, data models, technical specifications, and delivery plans.
- Strong analytical, troubleshooting, documentation, consulting, and stakeholder management skills.
- Ability to provide technical leadership across multiple teams while remaining hands on.
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related discipline.
- Nice to have: Experience working with investment management, asset management, fixed income, financial products, risk, compliance, or distribution datasets.
- Experience with Microsoft Purview, Azure Data Lake Storage, Azure Data Factory, Azure Synapse Analytics, Azure Key Vault, and Azure Monitor.
- Experience integrating Microsoft Fabric with Snowflake, Databricks, Oracle, SQL Server, or other enterprise data platforms.
- Experience migrating legacy data warehouses, Power BI solutions, Azure Synapse, or Azure Data Factory workloads to Microsoft Fabric.
- Knowledge of data mesh, domain oriented architecture, data products, and federated governance.
- Experience with real time intelligence, event streaming, or operational analytics.
- Familiarity with TMDL, PBIP, Tabular Editor, XMLA endpoints, or semantic model automation.
- Relevant Microsoft Fabric, Power BI, Azure Data, or architecture certifications.

📌 Fabric Architect (Bengaluru)
🏢 DataArt
📍 Bengaluru