Principal Data Engineer
Apache Kafka, Big Data, Architectural Design, Technical Contribution, AWS, JavaSCript, Node
Who are we?
Moneyhub empowers financial services firms with complete, detailed, and real-time insight into their customers’ financial needs and status, enabling them to take informed actions. Our highly categorised, data-enriched analytics allow clients to craft personalised customer journeys, leading to enhanced engagement, optimised acquisition and servicing costs, and increased conversion rates.
As an established B2B2C company, our clients roll out our technology to improve their customers journey and enhance their financial outcomes. We do this through an API and embedded experience approach that streamlines access to our market-leading Journeys, Categorisation, Decisioning, and Analytics engines, together with Payments Initiation. In doing so we deliver actionable insights with reduced transaction costs, accelerated settlements, and a safer, more convenient customer experience.
We’re a regulated entity offering AISP, PISP, and CISP services, trusted by leading banks, insurers, asset and wealth managers, pension companies, financial advisors, and fintechs to enhance financial outcomes for their clients.
💰 What do we offer?
We have offices in London and Bristol together with access to co-working space across the UK. We offer the opportunity to work remotely within in the UK (role, business and client dependent) with support for your home office set-up if required. We have regular all company away days and other company, client and team meetings, your attendance at which will be mandatory.
Benefits include for this role include:
- 5% company contribution towards your Pension from your very first day with us. 3% contribution from yourself.
- 25 days of holiday (plus bank hols), rising to 30 days after two years;
- Choose to take your entitlement to UK bank holidays at other times based on your own days of significance;
- Private medical insurance, including cover for pre-existing conditions, plus dental and optical benefit;
- 3 Months Moneyhubber Family Pay when you become a new parent;
- Permanent health insurance and life cover - much greater than the industry standard (death in service);
- Employee assistance programme;
- Professional development support, with dedicated allowance of time and money; Life event leave;
- Cycle to work scheme;
- EV Car Scheme
- £750 towards professional memberships
- Remote working benefits, including work from almost anywhere, access to co-working spaces and support for your home office set-up
- High spec laptop
Requirements
As a Principal Data Engineer at Moneyhub, you'll join a team of senior engineers to provide the crucial, deep expertise needed to evolve our most demanding data systems. You will be the technical authority for our high-performance data enrichment engine, a Kafka-based platform that processes tens of thousands of transactions per second. We deploy this engine directly into our enterprise clients' cloud environments and also run it as a service for major financial services customers.
This is a senior individual contributor role for someone who has lived the challenges of engineering for scale. You will use your experience to provide technical leadership, bridging the gap between complex software engineering and scalable cloud infrastructure to ensure our core data services are robust, efficient, and future-proof.
What You'll Work On- Evolve a Mission-Critical System: Take technical ownership of our Kafka-based Data Enrichment Engine, a platform that runs multiple analytical models at 20,000+ transactions per second.
- Architect for Scale: Design and implement architectural improvements to enhance the platform's performance, reliability, and scalability across both our SaaS and client-deployed environments.
- Solve Complex Engineering Challenges: Tackle deep technical problems related to high-throughput data ingestion, distributed systems, data consistency, and operational efficiency in a live production environment.
- Act as the Subject Matter Expert (SME): As the go-to expert for the toughest data infrastructure challenges, you'll partner closely with our DevSecOps team to ensure production excellence. You will guide and mentor other engineers, establishing best practices for building and operating large-scale data systems.
- Leader of the design and development of large-scale data systems from scratch, making key design decisions and providing technical oversight of projects.
- Expert-level, hands-on experience with Apache Kafka, including designing, deploying, and operating it in a high-throughput production environment.
- Experience designing, managing, and running relational databases at a terabyte scale.
- Deep knowledge of how technologies such as Apache Spark, BigQuery or AWS Athena work including principles such as map/reduce and schema-on-read.
- Strong software engineering fundamentals with proficiency in a backend language, preferably JavaScript/Node.js.
- Demonstrable experience building solutions on a major public cloud platform (GCP, AWS, or Azure) with an ability to price expected running costs of solutions
- A pragmatic and autonomous problem-solver who takes end-to-end ownership, can unblock themselves by digging into documentation, and knows when to create a simple solution vs. an architecturally complex one.
- You have a production-first mindset. You don't just build prototypes; you engineer resilient, observable, and production-grade services designed for the long haul, and you have a track record to prove it.
- You lead with expertise. You excel at guiding technical strategy and influencing your peers through deep knowledge and persuasive communication, not direct authority.
- You're comfortable with complexity. You have hands-on experience with modern cloud-native technologies, including containerization (Docker) and orchestration (Kubernetes), and know how to apply them effectively.
- You understand our domain. Previous experience in the FinTech industry gives you an edge, as you'll already be familiar with the unique security, compliance, and data sensitivity requirements of financial services.
