Data Engineer
关于 Ripjar,Ripjar 是由 GCHQ 的退伍军人创立，以为打击金融犯罪提供国家安全级情报工具。金融犯罪在全球范围内资助人口贩运，恐怖主义，腐败和逃避制裁，前线组织需要技术来匹配威胁。今天，RipJar 的人工智能原生软件和数据融合产品由各国政府，世界上最大的银行和全球企业用于自动检测，调查和监控严重金融犯罪。每天，数百名客户和数千名每日活跃用户依赖平台以实时检查数亿名字的风险，防止洗钱和阻止恐怖主义融资。如果你想让你的工作有意义，这就是发生的地方。我们是一个远程第一团队，总部设在切尔顿汉姆。这个职位是公开的英国范围内的候选人。如果你位于切尔顿哈姆附近，你可以随时从我们的办公室工作。关于角色 我们看到一个数据工程师作为专业于分布式数据系统的软件工程师。你将加入数据工程团队，其首要责任是开发和运营数据收集中心，这是一个从多个来源获取数据的平台，处理/丰富并分发到多种下游系统。我们正在寻找拥有2年以上行业经验在构建和运营生产软件的人，谁喜欢跨越数据管道，分布式系统和操作可靠性工作。你会做什么？· 设计和发展数据契约 （方案，验证规则，版本化，后期兼容性）,以便下游团队能够自信地构建。· 自有生产质量：编写可维护的代码，强大的单元/集成测试，并添加你需要的可观测性 （计量表/日志/追踪）来快速诊断问题。·通过加强对部分故障，重复尝试，速度限制，数据漂移和基础设施问题的管道进行稳定来提高平台可靠性。
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About Ripjar
Ripjar was founded by veterans of GCHQ to bring national security-grade intelligence tools to the fight against financial crime. Financial crime funds human trafficking, terrorism, corruption and sanctions evasion on a global scale, and the organisations on the front line need technology built to match the threat.
Today, Ripjar's AI-native software and data fusion products are used by governments, the world's largest banks, and global enterprises to automate the detection, investigation and monitoring of serious financial crime. Every day, hundreds of customers and thousands of daily active users rely on the platform to screen hundreds of millions of names for risk in real time, prevent money laundering and stop terrorist financing.
If you want your work to matter, this is where it happens.
We are a remote first team, with a head office based in Cheltenham. This position is open to UK wide candidates. If you are based near Cheltenham, you are more than welcome to work from our office at any time.
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)
Requirements
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
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.
Originally posted on Himalayas