Director – Head of Data Transformation (Insurance / Banking, Snowflake)

Gazelle Global

London

2 days ago

Applications closed

Related Jobs

View all jobs

Head of Data Analytics

Head of Data Governance

Beauty & Wellbeing Business Intelligence Director

Director, Data Visualization & Automation

Data science programme lead, hireful

Data science programme lead

Overview

Director – Data Transformation (Insurance / Banking, Snowflake) to lead a high-profile data-driven transformation programme for an Insurance client. The ideal candidate will bring strong banking experience, hands-on expertise in data platform transformation, and proven success in the Insurance / Lloyd’s of London Market domain. This role requires the ability to strategically influence at executive level while remaining hands-on in delivery, ensuring successful programme execution and stakeholder alignment.

Key Responsibilities

Lead end-to-end delivery of strategic data transformation programmes across insurance and banking domains.
Collaborate with senior stakeholders, Data Governance, and business leaders to drive the change roadmap.
Provide hands-on leadership in programme execution, managing delivery teams and vendors.
Monitor programme performance, ensuring scope, budget, and quality standards are met.
Act as the key liaison between business and technology, aligning data initiatives with organisational strategy.
Present regular updates and strategic insights to executive-level stakeholders.
Ensure compliance with regulatory requirements and best practices in data governance.
Oversee vendor partnerships, resourcing, and cross-functional collaboration.

Skills & Experience Required

VP-level experience in programme delivery within Banking and/or Insurance (Lloyd’s of London experience preferred).
Proven expertise in data-driven transformation projects, including Snowflake and modern data platforms.
Strong knowledge of relational databases (Oracle, SQL Server, PostgreSQL).
Excellent stakeholder management and communication skills at senior (C/Board) level.
Experience managing vendors and large-scale transformation initiatives.
Knowledge of tools such as Python and Power BI desirable.
Strong business acumen, risk management, and ability to influence strategic direction.

Why Join?

Lead a strategic data transformation initiative in the Insurance sector.
Operate at VP level, shaping both delivery and strategy.
Opportunity to leverage both banking and insurance experience in a high-impact role.
Flexible hybrid working model (London, 2–3 days onsite).

Seniority level

Mid-Senior level

Employment type

Contract

Job function

Information Technology and Management
Industries: Insurance

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Feb 3, 2026

Jobs

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

Jan 23, 2026

Education

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

Jan 18, 2026

Careers Jobs

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.