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- 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, and private healthcare.
- Why this job: Make a real impact by working with cutting-edge technology in a meaningful field.
- Qualifications: 2+ years in software engineering, strong programming skills, and data system experience.
- Other info: Enjoy remote work, a supportive culture, and excellent career growth opportunities.
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 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)
Requirements
- Essential: 2+ years building and operating production software systems
- Fluency in at least one programming language 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
Benefits
- 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 employer: Ripjar
Contact Detail:
Ripjar Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to data engineering. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the company’s tech stack. Practice common data engineering problems and be ready to discuss how you've tackled challenges in past roles.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Engineer
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, Spark, or Kubernetes. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about combating financial crime and how your background makes you a great fit for our team. Keep it engaging and personal – we love to see your personality!
Showcase Your Projects: If you've worked on any projects that involved data pipelines or operational reliability, make sure to mention them. We want to know about your hands-on experience and how you've tackled real-world challenges in your previous roles.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen to join our team at Ripjar!
How to prepare for a job interview at Ripjar
✨Know Your Tech Stack
Familiarise yourself with the technologies mentioned in the job description, especially Python, Spark, and Kubernetes. Be ready to discuss your experience with these tools and how you've used them in past projects.
✨Showcase Problem-Solving Skills
Prepare to talk about specific challenges you've faced in data engineering. Highlight how you approached these problems, the solutions you implemented, and the impact they had on the project or team.
✨Understand Data Reliability
Since the role focuses on operational reliability, be prepared to discuss how you've ensured data quality and reliability in your previous work. Share examples of how you've handled edge cases and improved system performance.
✨Engage in Collaborative Discussions
The interview may involve design reviews or discussions about trade-offs. Practice articulating your thought process clearly and be open to feedback. Show that you can collaborate effectively with others to achieve common goals.