Head of Enterprise Data & System Integration Banking Hybrid

Tonbridge
8 months ago
Applications closed

Related Jobs

View all jobs

Head of DevOps and DataOps

Data Engineer

Data Engineer

Data Engineer (18 Months FTC)

Lead Data Engineer

Senior Data Engineer

A leading Bank is seeking a Head of Enterprise Data & System Integration on a permanent basis.

This role will operate on a 4 day working week basis and you will need to attend the Kent office at least twice a week. You will be needed onsite full time during the induction period.

The Role

Build and lead a bank-wide data and systems integration function to deliver a trusted single source of truth for internal (operational performance, strategic decisions), external (including client interactions/campaigns, regulatory, financial, and impact), and stakeholder reporting. Build the data capability and architecture to support high-quality insight, strategic decision-making, client engagement, business performance, and risk management. Drive up maturity in data quality, culture, and accountability. Align systems and data flows to enable efficient operations, scalable data access, and innovation across the organization.

Experience Required:

  • Significant experience in leading enterprise data strategy, system integration, and governance within a regulated environment — ideally financial services.

  • Proven track record of delivering scalable data platforms and tools that support operational and analytical use cases.

  • Involvement in implementing or transitioning to Data Mesh or federated data ownership models.

  • Experience in managing, mentoring, or building a cross-functional data team.

  • Experience in using data to drive deeper customer insight, segmentation, and service personalisation to support commercial and social outcomes.

  • Strong attention to detail and ability to ensure both strategy and execution are carried through to a high standard.

  • Experience in the definition and execution of enterprise-wide data governance frameworks, controls, and policy

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

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

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

Careers

How Many Data Engineering Tools Do You Need to Know to Get a Data Engineering Job?

If you’re aiming for a career in data engineering, it can feel like you’re staring at a never-ending list of tools and technologies — SQL, Python, Spark, Kafka, Airflow, dbt, Snowflake, Redshift, Terraform, Kubernetes, and the list goes on. Scroll job boards and LinkedIn, and it’s easy to conclude that unless you have experience with every modern tool in the data stack, you won’t even get a callback. Here’s the honest truth most data engineering hiring managers will quietly agree with: 👉 They don’t hire you because you know every tool — they hire you because you can solve real data problems with the tools you know. Tools matter. But only in service of outcomes. Jobs are won by candidates who know why a technology is used, when to use it, and how to explain their decisions. So how many data engineering tools do you actually need to know to get a job? For most job seekers, the answer is far fewer than you think — but you do need them in the right combination and order. This article breaks down what employers really expect, which tools are core, which are role-specific, and how to focus your learning so you look capable and employable rather than overwhelmed.

Jobs

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

If you’re applying for data engineering jobs in the UK, the first thing to understand is this: Hiring managers don’t read every word of your CV. They scan it. They look for signals of relevance, credibility, delivery and collaboration — and if they don’t see the right signals quickly, your application may never get a second look. In data engineering, hiring managers are especially focused on whether you can build and operate reliable, scalable data systems, handle real-world data challenges and work effectively with analytics, BI, data science and engineering teams. This guide breaks down exactly what they look at first in your application — and how to shape your CV, portfolio and cover letter so you stand out.

Education

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

Data engineering has quietly become one of the most critical roles in the modern technology stack. While data science and AI often receive the spotlight, data engineers are the professionals who design, build and maintain the systems that make data usable at scale. Across the UK, demand for data engineers continues to rise. Organisations in finance, retail, healthcare, government, media and technology all report difficulty hiring candidates with the right skills. Salaries remain strong, and experienced professionals are in short supply. Yet despite this demand, many graduates with degrees in computer science, data science or related disciplines struggle to secure data engineering roles. The reason is not academic ability. It is a persistent skills gap between university education and real-world data engineering work. This article explores that gap in depth: what universities teach well, what they consistently miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data engineering.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.