Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Principal Data Engineer - HSBC

HSBC
Birmingham
2 days ago
Create job alert

If you're looking for a career where you can make a real impression, join HSBC and discover how valued you'll be.

HSBC is one of the largest banking and financial services organisations in the world, with operations in 64 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people to fulfil their hopes and realise their ambitions.

We are currently seeking an experienced professional to join our team in the role of The Principal Cybersecurity Data Engineer, this a key technical role within the Platform & Data Engineering Team, contributing to, coordinating, and leading data engineering, data acquisition, cloud infrastructure and platform engineering, platform operations, and production support activities using ground-breaking cloud and big data technologies.

The position is a senior technical, hands-on delivery role, requiring knowledge of data engineering, cloud infrastructure and platform engineering, platform operations and production support

As an HSBC employee in the UK, you will have access to tailored professional development opportunities and a competitive pay and benefits package. This includes private healthcare for all UK-based employees, enhanced maternity and adoption pay and support when you return to work, and a contributory pension scheme with a generous employer contribution.

In this role you will:

  • Ingest and provision raw datasets, enriched tables, and curated data assets to support various cybersecurity use cases.
  • Drive enhancements to the data ingestion process, with an emphasis on real-time data coverage.
  • Design and implement robust data pipelines that integrate diverse data sources across the enterprise and external platforms.
  • Perform ETL workflows, leveraging both advanced data manipulation tools and custom code, ensuring data is accessible and structured appropriately for all systems and stakeholders.
  • Identify, analyze, and onboard new data sources, conducting exploratory analysis when necessary.



To be successful in this role you should meet the following requirements:

  • Strong experience with SRE and Azure DevOps.
  • Proficiency in scripting (Bash/PowerShell, Azure CLI), coding (Python, C#, Java), and querying (SQL, Kusto).
  • Hands-on experience with PowerShell, Terraform, and object-oriented programming languages.
  • Strong experience with cloud & big data technologies, including Azure Cloud, Azure IAM, Azure AD, Azure Data Factory, Databricks, Kubernetes, and PowerBI.
  • Experience with server and infrastructure technologies like Nginx/Apache, CosmosDB, Linux, and tools such as Prometheus, Grafana, and Elasticsearch.



This role is based in Sheffield or Birmingham

Opening up a world of opportunity

Being open to different points of view is important for our business and the communities we serve. At HSBC, we're dedicated to creating diverse and inclusive workplaces - no matter their gender, ethnicity, disability, religion, sexual orientation, or age. We are committed to removing barriers and ensuring careers at HSBC are inclusive and accessible for everyone to be at their best. We take pride in being a Disability Confident Leader and will offer an interview to people with disabilities, long term conditions or neurodivergent candidates who meet the minimum criteria for the role.

Related Jobs

View all jobs

Principal Data Engineer/Architect

Principal Data Engineer - HSBC

Principal Data Engineer

Principal, Data Engineering (Remote)

Principal Data Engineer

Principal Data Engineer

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.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.