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AI Summary
Lead the design and implementation of scalable cloud data platforms and enterprise-grade BI solutions. Responsible for building ELT pipelines, semantic models, and optimizing performance across SQL workloads and Power BI dashboards.
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
- Data warehouse / lakehouse layers
- 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
- SQL workloads and data pipelines
- 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)
- Microsoft Fabric (Lakehouse, Dataflows, Pipelines)
- Very strong SQL expertise (mandatory):
- Complex transformations, query optimization, and performance tuning
- Experience handling large-scale, high-volume datasets
- Complex transformations, query optimization, and performance tuning
- Deep expertise in Data Modelling (mandatory):
- Dimensional modelling (star/snowflake schema)
- Normalization vs denormalization strategies
- Semantic layer design for analytics
- Dimensional modelling (star/snowflake schema)
- Strong Data Warehousing experience (mandatory):
- Designing and implementing enterprise-grade data warehouses
- Strong understanding of Kimball/Inmon methodologies
- Experience with lakehouse architectures
- Designing and implementing enterprise-grade data warehouses
- 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)
- End to end development expertise
- 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)
- Data orchestration tools (e.g., Azure Data Factory / Synapse or equivalent)
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. At Exavalu, we are committed to building a diverse and inclusive workforce. We welcome applications for employment from all qualified candidates, regardless of race, colour, gender, national or ethnic origin, age, disability, religion, sexual orientation, gender identity or any other status protected by applicable law. We nurture a culture that embraces all individuals and promotes diverse perspectives, where you can make an impact and grow your career
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