The Role
Leads the design and delivery of enterprise data platforms, lakehouses, warehouses, data pipelines, models, and Power BI solutions. Responsibilities include data ingestion and transformation, semantic modeling, performance optimization, governance, lineage, security, stakeholder collaboration, and technical leadership across data engineering and BI workstreams. The role also drives DevOps and CI/CD practices for data and analytics deployments.
Summary Generated by Built In
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)
- 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
RequirementsRequired 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)
- Exposure to AI / GenAI / Agentic AI concepts in data and analytics workflows
- Experience with Tableau
- 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
Skills Required
- 10+ years of experience in data engineering, data warehousing, business intelligence, or analytics
- Hands-on expertise with at least one of Microsoft Fabric, Azure Databricks, or Snowflake
- Very strong SQL expertise, including complex transformations, query optimization, and performance tuning
- Experience handling large-scale, high-volume datasets
- Deep expertise in data modeling, including dimensional modeling, normalization, denormalization, and semantic layer design
- Strong experience designing and implementing enterprise-grade data warehouses
- Understanding of Kimball and Inmon data warehousing methodologies
- Experience with lakehouse architectures
- Strong Power BI experience, including semantic models, reports, dashboards, advanced DAX, Power Query, and performance tuning
- Experience with data orchestration tools such as Azure Data Factory, Azure Synapse, or equivalent
- Experience with Python or PySpark for data processing
- Experience with CI/CD and DevOps practices for data and analytics solutions
- Experience with data governance, lineage, and security, including RLS and OLS
- Exposure to AI, GenAI, or Agentic AI concepts in data and analytics workflows
- Experience with Tableau
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The Company
What We Do
Exavalu leads the way in business and technology consulting and solution delivery, focusing on specialized digital transformation across the Insurance, Healthcare & Life Sciences, and Nonprofit industries. As an award-winning digital transformation advisor, we take pride in delivering leading-edge solutions to clients worldwide. Led by industry veterans and technology experts, we bring our deep understanding in customer experience, process automation, digital engineering, cloud, data and AI with a very strong industry core foundation. Drawing on our industry insights and technological acumen, we enable clients to drives growth, profitability, and cost optimization. We mitigate risks and elevate customer experience through our comprehensive suite of services, including strategic advisory, expert-led technology [build and maintenance], and best-in-class products and solutions. Our unwavering focus on understanding the industry's hard problems and finding the right solution has garnered recognition as the preferred ally for organizations seeking transformative growth.
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