Data & BI Lead

This is a remote position. **Overview :** We are seeking a Data & BI Lead with 10+ years of experience across data engineering, data warehousing, and business intelligence. This role requires strong hands-on expertise in modern cloud data platforms such as Microsoft Fabric, Azure Databricks, or Snowflake, along with deep experience in Power BI for building enterprise-grade analytical solutions. The ideal candidate will lead and deliver end-to-end data platforms and BI solutions, with equal depth in data engineering, data modelling, and BI engineering (Power BI) * * * ### Key Responsibilities: - Lead design and implementation of scalable data platforms (lakehouse / warehouse) on Microsoft Fabric, Azure Databricks, or Snowflake - Build and optimize data ingestion, transformation, and ELT pipelines for large-scale data processing - Design and implement enterprise data models across: - Data warehouse / lakehouse layers - Analytical / semantic layers for reporting - Develop and maintain Power BI datasets, semantic models, and dashboards aligned with enterprise standards - Drive query and performance optimization across: - SQL workloads and data pipelines - BI semantic layer and reporting performance - Establish data warehousing standards, modelling frameworks, and reusable data assets - Ensure data quality, governance, lineage, and security across the platform - Collaborate with stakeholders to translate business requirements into scalable data and analytics solutions - Provide technical leadership across both data engineering and BI workstreams - Drive DevOps and CI/CD practices for data pipelines and BI deployments ### Requirements ### Required Skills & Experience: - 10+ years in Data Engineering, Data Warehousing, BI, or Analytics - Strong hands-on expertise in data engineering on at least one platform (mandatory): - Microsoft Fabric (Lakehouse, Dataflows, Pipelines) - Azure Databricks (PySpark, Delta Lake, distributed processing) - Snowflake (ELT design, performance optimization, data modelling) - Very strong SQL expertise (mandatory): - Complex transformations, query optimization, and performance tuning - Experience handling large-scale, high-volume datasets - Deep expertise in Data Modelling (mandatory): - Dimensional modelling (star/snowflake schema) - Normalization vs denormalization strategies - Semantic layer design for analytics - Strong Data Warehousing experience (mandatory): - Designing and implementing enterprise-grade data warehouses - Strong understanding of Kimball/Inmon methodologies - Experience with lakehouse architectures - Strong Power BI experience (mandatory): - End to end development expertise - Building semantic models, reports, and dashboards - Advanced DAX and Power Query (M) - Performance tuning (aggregations, incremental refresh, composite models) - Experience with: - Data orchestration tools (e.g., Azure Data Factory / Synapse or equivalent) - Python / PySpark for data processing - CI/CD and DevOps practices for data and analytics solutions - Data governance, lineage, and security (including RLS/OLS) * * * ### Good to Have: - Exposure to AI / GenAI / Agentic AI concepts in data and analytics workflows - Experience with Tableau * * * ### Ideal Candidate Profile: - Strong foundation in data engineering, data modelling, and BI engineering - Capable of designing and building both backend data platforms and frontend analytical solutions - Comfortable working across architecture, development, and delivery - Effective in engaging with both business stakeholders and technical teams - Focused on scalability, performance, and long-term maintainability ### Benefits Diversity Inclusion: Exavalu also promotes flexibility, adapting to the needs of employees, customers, and the business. It might be part-time work, working outside normal 9-5 business hours or working remotely. We also offer a welcome back program to help individuals return to the mainstream after a prolonged absence due to health or family reasons…