Position Description
Data Platform Technical Lead (Microsoft Fabric & Power BI)
Department: Technology / Data & Analytics
Reports to: Data & Quality Lead
Location: Remote
Employment Type: Permanent, Full‑time
Role Purpose
The Data Platform Technical Lead is accountable for the end‑to‑end ownership of CXC's Data & Analytics Platform, built on Microsoft Fabric and Power BI.
This role is the hands‑on technical authority responsible for how data is ingested, transformed, modelled, governed, and consumed across the organisation. The role spans the full lifecycle — from raw source data through to executive, operational, and client‑facing dashboards.
Reporting to the Data & Quality Lead, with a dotted‑line relationship to the Solution Architect, this role ensures the data platform is robust, scalable, performant, and aligned to enterprise architecture standards, while remaining highly delivery‑focused and pragmatic.
The role acts as the technical lead for data across the wider Technology group, supporting multiple teams and initiatives rather than operating as a siloed reporting or BI function.
Role Scope
This role owns how the data platform is implemented and operated.
- Strategic prioritisation, data quality governance, and business ownership sit with the Data & Quality Lead
- Enterprise‑wide architectural standards and patterns are governed by the Solution Architect
- This role is accountable for designing, building, running, and evolving the data platform itself
Key Responsibilities
1. End‑to‑End Platform Ownership
- Own the full Microsoft Fabric and Power BI platform across all layers.
- Be accountable for platform stability, performance, scalability, and cost efficiency.
- Act as the single technical point of ownership for the data platform.
2. Data Ingestion & Orchestration
- Design, build, and maintain data ingestion pipelines using Azure Data Factory and Fabric Pipelines.
- Ingest data from multiple source systems including operational, finance, payroll, and core platforms.
- Implement structured raw ingestion layers within OneLake.
- Ensure ingestion processes are reliable, auditable, and resilient to change.
3. Spark & Transformation Layer
- Build and own Spark Notebooks for data cleansing, transformation, and standardisation.
- Implement and maintain complex business logic, including:
- Data mappings
- Standardisation rules
- Enrichment logic
- Optimise Spark workloads for performance and cost.
- Ensure transformation logic is documented, testable, and reusable.
4. Common Data Model & Semantic Layer
- Design and own the Common Data Model used across the organisation.
- Build and maintain Fabric Semantic Models that:
- Support multiple reporting use cases
- Enable reuse and consistency
- Balance flexibility with governance
- Define conformed dimensions, measures, and naming standards.
- Act as the authority on data definitions and meaning.
5. Power BI & Reporting Enablement
- Act as the Power BI technical expert across CXC.
- Design and support:
- Executive dashboards
- Operational and management reporting
- Client‑facing dashboards and report variants
- Support paginated reporting where required.
- Ensure reporting performance, scalability, and consistent user experience.
6. Technical Leadership & Cross‑Team Support
- Act as the technical data lead supporting the wider Technology group.
- Partner with delivery teams, solution architects, and business stakeholders.
- Review and shape data‑related design decisions across platforms and initiatives.
- Translate business requirements into scalable, maintainable data solutions.
7. Governance, Standards & Quality
- Define and enforce technical standards for:
- Data modelling
- Semantic layer design
- Naming conventions
- Reuse and layering
- Work with the Data & Quality Lead to ensure outputs meet governance and audit expectations.
- Champion data lineage, transparency, and clarity across the platform.
8. Continuous Improvement
- Identify and reduce manual effort through automation and reuse.
- Simplify and standardise data pipelines and reporting patterns.
- Support experimentation and innovation while protecting platform stability.
- Continuously evolve the platform to meet changing business needs.
Skills & Experience
Essential
- Expert‑level experience with Power BI, including modelling, DAX, and performance optimisation.
- Deep hands‑on experience with Microsoft Fabric.
- Strong experience with Spark (PySpark and/or SQL).
- Proven experience with Azure Data Factory / Fabric Pipelines.
- Advanced skills in:
- Data modelling and mapping
- Semantic model design
- Lakehouse architectures
- Demonstrated ability to own and operate complex data platforms end‑to‑end.
Desirable
- Experience supporting client‑facing reporting platforms.
- Exposure to finance, payroll, or workforce data domains.
- Experience working in global, multi‑region environments.
- Familiarity with governance, audit, or compliance requirements.
- Exposure to AI‑enabled analytics or advanced data use cases.
Personal Attributes
- Strong sense of ownership and accountability.
- Comfortable operating independently with minimal supervision.
- Pragmatic and delivery‑focused, avoiding over‑engineering.
- Able to explain complex technical concepts to non‑technical stakeholders.
- Natural technical leader without reliance on authority or hierarchy.
What Success Looks Like
- A stable, scalable data platform trusted by the business.
- Reduced manual data preparation and rework.
- Consistent, reusable semantic models across reporting.
- Faster delivery of high‑quality insights to stakeholders.
- Clear technical leadership and reduced dependency bottlenecks.
