At a Glance
- Tasks: Engineer data systems to combat financial crime and enhance operational reliability.
- Company: Join Ripjar, a leader in software and data products for fighting financial crime.
- Benefits: Competitive salary, 25 days leave plus your birthday off, remote work, and private healthcare.
- Other info: Dynamic team environment with excellent career growth and the latest tech tools.
- Why this job: Make a real impact by working with diverse datasets and cutting-edge technology.
- Qualifications: 2+ years in software engineering, fluency in Python or Node.js, and strong debugging skills.
The predicted salary is between 36000 - 60000 £ per year.
About Ripjar
Ripjar specialises in the development of software and data products that help governments and organisations combat serious financial crime. Our technology is used to identify criminal activity such as money laundering and terrorist financing, enabling organisations to enforce sanctions at scale to help combat rogue entities and state actors. Data infuses everything Ripjar does. We work with a wide variety of datasets of all scales, including an ever‑growing archive of billions of news articles covering most languages going back over 30 years, sanctions and watchlist data provided by governments, and vast organisation and ownership datasets.
About the Role
We see a Data Engineer as a software engineer who specialises in distributed data systems. You’ll join the Data Engineering team, whose prime responsibility is the development and operation of the Data Collection Hub, a platform that ingests data from many sources, processes/enriches it, and distributes it to multiple downstream systems. We’re looking for someone with 2+ years of industry experience building and operating production software who enjoys working across data pipelines, distributed systems, and operational reliability.
What you’ll do
- Engineer distributed ingestion services that reliably pull data from diverse sources, handle messy real‑world edge cases, and deliver clean, well‑structured outputs to multiple downstream products.
- Build high‑throughput processing components (batch and/or near‑real‑time) with a focus on performance, scalability, and predictable cost, using strong profiling and measurement practices.
- Design and evolve data contracts (schemas, validation rules, versioning, backward compatibility) so downstream teams can build with confidence.
- Own production quality: write maintainable code, strong unit/integration tests, and add the observability you need (metrics/logs/tracing) to diagnose issues quickly.
- Improve platform reliability by hardening pipelines against partial failures, retries, rate limits, data drift, and infrastructure issues—then codify those learnings into better tooling and guardrails.
- Contribute to CI/CD and developer experience: faster builds, better test signal, safer releases, and automated operational checks.
- Participate in design reviews, code reviews, incident retrospectives, and iterative delivery—making pragmatic trade‑offs and documenting them clearly.
Technology Stack
- Languages: Predominantly Python and Node.js
- Distributed/data platforms: HDFS, HBase, Spark, plus increasing use of Kubernetes and cloud services
- Storage/search: MongoDB, OpenSearch
- Orchestration: Airflow, Dagster, NiFi
- Tooling: GitHub, GitHub Actions, Rundeck, Jira, Confluence
- Deployment/config: Ansible (physical), Terraform / Argo CD / Helm (Kubernetes)
- Development environment: MacBook (typical)
Essential:
- 2+ years building and operating production software systems
- Fluency in at least one programming language (Python/Node.js a plus)
- Experience debugging moderately complex systems and improving reliability/performance
- Strong fundamentals: data structures, testing, version control, Linux basics
Nice to have:
- Spark/PySpark experience
- Hadoop ecosystem exposure (HDFS/HBase)
- Workflow orchestration (Airflow/Dagster/NiFi)
- Search/indexing (OpenSearch, MongoDB)
- Kubernetes and infrastructure‑as‑code
- Degree in Computer Science or numerical degree
Competitive salary DOE
25 days annual leave + your birthday off, in addition to bank holidays, rising to 30 days after 5 years of service.
Remote working
Private Family Healthcare.
35 hour working week.
Employee Assistance Programme.
Company contributions to your pension.
Pension salary sacrifice.
Enhanced maternity/paternity pay.
The latest tech including a top of the range MacBook Pro.
Data Engineer in Cheltenham employer: Ripjar Ltd
Ripjar is an exceptional employer that prioritises innovation and employee well-being, offering a competitive salary and a generous benefits package including 25 days of annual leave plus your birthday off, rising to 30 days after five years. With a strong focus on professional growth, employees are encouraged to engage in continuous learning and development within a collaborative work culture that values diversity and creativity, all while working remotely with cutting-edge technology.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer in Cheltenham
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with current employees at Ripjar. A friendly chat can sometimes lead to opportunities that aren’t even advertised!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving data pipelines or distributed systems. This gives us a tangible way to see what you can do beyond just words on a CV.
✨Tip Number 3
Prepare for the technical interview! Brush up on your Python and Node.js skills, and be ready to discuss your experience with data structures and debugging. We love seeing how you tackle real-world problems.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at Ripjar.
We think you need these skills to ace Data Engineer in Cheltenham
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Engineer role. Highlight your experience with distributed data systems and any relevant technologies like Python or Node.js. We want to see how your skills match what we're looking for!
Showcase Your Projects:Include specific projects that demonstrate your ability to build and operate production software. If you've worked on data pipelines or improved system reliability, let us know! Real-world examples can make a big difference.
Be Clear and Concise:When writing your application, keep it clear and to the point. Use bullet points where possible to make it easy for us to read. We appreciate straightforward communication, especially when it comes to technical details.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role. Don’t miss out on this opportunity!
How to prepare for a job interview at Ripjar Ltd
✨Know Your Tech Stack
Familiarise yourself with the technologies mentioned in the job description, especially Python and Node.js. Be ready to discuss your experience with distributed systems, data pipelines, and any relevant tools like Spark or Kubernetes. This shows you’re not just a fit on paper but also understand the practical applications.
✨Showcase Problem-Solving Skills
Prepare examples of how you've tackled complex issues in previous roles. Think about times when you improved system reliability or performance. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it easy for the interviewer to follow your thought process.
✨Understand Data Contracts
Since the role involves designing data contracts, brush up on schemas, validation rules, and versioning. Be prepared to discuss how you’ve implemented these in past projects and how they can impact downstream teams. This will demonstrate your understanding of the bigger picture in data engineering.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the team’s current challenges, the tech stack, or how they measure success in the Data Engineering team. This not only shows your interest but also helps you gauge if the company is the right fit for you.
