Data Team Lead

La Fosse; Poole; Hybrid; GBP 80,000 - 100,000; Full time

Job summary

A well-established charity organization is seeking a Data Workstream Lead for a 6-month contract to oversee data delivery in a major ERP transformation. This role involves leading end-to-end data migration, ensuring data quality, and acting as the liaison between technical teams and stakeholders. Ideal candidates should have a strong background in data engineering and extensive experience with Databricks, with the ability to communicate effectively with non-technical stakeholders. The position offers a day rate of £550 - £600 and the flexibility of remote work after an initial month on-site.

Qualifications

• 5+ years of experience in data engineering or technical roles.
• Deep understanding of data migration strategies and data quality frameworks.
• Experience in communication with non-technical stakeholders.

Responsibilities

• Lead the data workstream across the full ERP transformation lifecycle.
• Own end-to-end data migration and establish data governance.
• Translate business requirements into clear data models and reporting outputs.

Skills

Experience within the charity, public sector

Strong hands-on experience with Databricks

Background in data engineering or analytics engineering

Ability to communicate complex data concepts clearly

Tools

Databricks

Job description

Data Workstream Lead (Charity Sector)

Location: Poole (1 day a week for 1 month then more flexibility)

Contract: 6 month contract

Sector: Charity / Not-for-Profit / Digital Transformation

Day Rate: £550 - £600 per day Outside IR35

Company Overview

La Fosse is working with a well‑established charity organisation undergoing a major digital and ERP transformation. With a mission‑driven culture, they are investing in modern data capabilities and systems to better support the communities they serve. This role offers the chance to make a real impact at a pivotal point in their digital journey.

Role Overview

La Fosse is supporting the search for a Data Workstream Lead to own and drive all data‑related delivery across a large‑scale ERP transformation. This role will lead the design, migration, governance, and operationalisation of ERP data, working across platforms such as Workday or Dynamics 365 (D365) and Databricks.

The role acts as a critical interface between data engineering teams, ERP vendors, and business stakeholders - ensuring data is accurate, governed, trusted, and fit for both operational and analytical use. It is ideally suited to candidates with a strong data engineering or technical background who have progressed into programme or transformation roles.

Key Responsibilities

• Lead the data workstream across the full ERP transformation lifecycle, from discovery through post‑go‑live stabilisation.
• Own end‑to‑end data migration, including source‑to‑target mapping, profiling, cleansing, transformation logic, validation, reconciliation, and cutover planning.
• Define and deliver data architecture and migration approaches aligned to ERP and analytics platforms.
• Work closely with data engineering teams leveraging Databricks (notebooks, Delta Lake, pipelines) to build scalable ingestion, transformation, and validation processes.
• Translate business and operational requirements into clear data models, datasets, and reporting outputs.
• Establish and embed data governance, documentation, lineage, quality controls, and auditability across ERP data domains.
• Act as the data SME for ERP data structures, integrations, reporting, and downstream analytics consumption.
• Manage risks, dependencies, timelines, and quality metrics for all data deliverables within the wider programme.

Candidate Profile

Essential

• Experience within the charity, public sector
• Strong, hands‑on experience with Databricks, including pipelines, notebooks, and Delta tables.
• Background in data engineering, analytics engineering, or technology, with experience operating in business‑facing or transformation leadership roles.
• Deep understanding of data migration strategies, data quality frameworks, governance models, and end‑to‑end data lifecycle management.
• Ability to communicate complex data concepts clearly to senior, non‑technical stakeholders.