Lead Data & AI Delivery Consultant

Posted 7 hours 2 minutes ago by iBSC

£450 Annual
Contract
Not Specified
Factory Jobs
Yorkshire, Sheffield, United Kingdom, S5 9
Job Description

Job Title: Lead Data & AI Delivery Consultant (Workforce Intelligence)
Location: Sheffield, UK (Hybrid - 2/3 days per week on-site) OR flexible frequent travel to Sheffield
Employment Type: Contract/Full-Time

About the Role

We are seeking a highly experienced Lead Data & AI Consultant to spearhead the delivery of cutting-edge Workforce Intelligence applications within the financial services sector.

This is not a pure hands-on coding role; it is a strategic technical leadership position that requires you to act as the critical bridge between client stakeholders (C-suite & SMEs), Data Scientists, AI Engineers, and multi-disciplinary delivery pods.

You will be responsible for the end-to-end governance of AI outputs-from use case prioritization and requirements validation to ensuring robust data lineage and access control across our Azure/Databricks ecosystem. Your deep understanding of Knowledge Graphs and Agentic AI will be essential in quality-assuring the work of our engineering teams.

Key Responsibilities

1. Technical Leadership & AI Governance

  • Lead the prioritization of data science use cases, ensuring the team focuses on high-impact, commercially viable problems rather than experimental "nice-to-haves."

  • Direct and quality-assure the technical outputs of Data Scientists and AI Engineers, with a specific focus on Knowledge Graph architecture, semantic layer design, and Agent AI frameworks.

  • Define and enforce best practices for data science workflows (experimentation, feature engineering, model validation) to ensure reproducibility and scalability.

2. Multi-Pod Coordination & Data Orchestration

  • Act as the primary data workstream coordinator across multiple delivery pods (scrum teams), managing cross-pod dependencies to ensure seamless data flow and integration.

  • Oversee the design and implementation of data pipelines within the Medallion Architecture (Bronze/Silver/Gold) on Databricks, ensuring that AI models are consuming high-quality, curated data.

3. Client Engagement & Stakeholder Management

  • Independently engage with client Subject Matter Experts (SMEs) to run discovery workshops, elicit complex business requirements, and translate them into technical epics and user stories.

  • Manage working-level expectations autonomously-clearly communicating trade-offs between technical feasibility, timeline, and budget to both business and technical stakeholders.

  • Act as the "trusted advisor" to the client, providing clear, confident communication regarding project progress, risks, and data governance constraints.

4. Data Governance & Financial Services Compliance

  • Champion data lineage, governance, and access control across the entire analytics life cycle. Ensure all solutions comply with strict financial services regulations regarding sensitive employee/workforce data.

  • Implement and oversee robust security protocols via Unity Catalog in Databricks to manage fine-grained access permissions.

Technical Environment

You will be leading teams that operate within the following ecosystem. You are not expected to code daily, but you must know these tools well enough to troubleshoot and guide engineers:

  • Core Platform: Databricks (Medallion Architecture), Unity Catalog.

  • Databases & Storage: Azure Blob Storage, Azure SQL DB, GCP Big Query, SQLite.

  • Integration: Azure Data Factory (ADF) for ETL/ELT orchestration.

  • Advanced AI: Graph Databases (eg, Neo4j), Agentic AI frameworks.

  • Functional Domain: Workforce Intelligence (Skills-taxonomy, attrition modelling, organizational network analysis).

Candidate Requirements Essential Experience & Skills

  • Proven Track Record: Extensive experience (8+ years) in data-centric roles, with at least 3 years specifically acting as a lead bridging Data Science and Business Strategy.

  • AI Workflow Expertise: Deep understanding of Data Science development cycles, MLOps, and how to quality-assure machine learning models.

  • Graph & Semantic Knowledge: Strong conceptual and practical knowledge of Knowledge Graphs; ability to direct engineers on entity resolution and relationship mapping.

  • Coordination Capability: Demonstrated success coordinating complex data workstreams across multiple, concurrent delivery teams (pods).

  • Client Delivery: Proven experience running client-facing workshops, validating requirements, and managing expectations independently (without senior management hand-holding).

  • Financial Services: Solid understanding of the regulatory landscape in FS regarding data privacy, lineage, and access controls.

Technical Proficiency (Hands-Off but Highly Literate)

  • Commercially experienced with Databricks and the Medallion data architecture.

  • Familiar with integration patterns using Azure Data Factory.

  • Conversant in modern database technologies ( Azure SQL, GCP BigQuery, Blob Storage ).

  • Understanding of Agent AI concepts and how they interact with structured/unstructured data.

Domain Expertise

  • Mandatory: Previous functional experience delivering Workforce Intelligence or HR analytics applications (eg, talent planning, skills gap analysis, internal mobility, or retention analytics).