Spectrum Search
Senior Data Engineer, AI and Data Products

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Spectrum Search is partnered with an early-stage AI technology company building data-intensive products for finance teams. The company is looking for a Senior Data Engineer to take ownership of production data infrastructure supporting AI and machine learning products, with scope to develop into a technical leadership role.
About the opportunity
This is a senior, hands-on engineering position working on the data foundations behind AI-powered financial software. The role combines production data engineering, data modelling, integrations and cloud infrastructure, with a particular focus on ensuring AI systems can retrieve and reason over complex financial data accurately.
You will join a small engineering team with significant ownership and report directly to the technology leadership. Over time, the position is expected to evolve from primarily individual contribution towards mentoring engineers and shaping the longer-term data architecture.
The role
You will own critical data engineering problems end to end, from ingesting customer data and developing integrations through to designing data models and operating the supporting infrastructure.
The environment is Python-led and includes graph databases, vector stores, SQL, PostgreSQL, Snowflake, Google Cloud Platform, retrieval-augmented generation and modern DevOps practices.
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I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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Key responsibilities
- Build, operate and improve production Python data pipelines using ETL and ELT patterns
- Develop connectors and API integrations across data warehouses, enterprise resource planning, accounting and billing systems
- Design data models and ontologies that support accurate AI retrieval and agent reasoning
- Work with graph databases and vector stores supporting retrieval-augmented generation workflows
- Own engineering work across data, infrastructure and DevOps from design through to production
- Maintain reliable cloud infrastructure, CI/CD pipelines, infrastructure as code and appropriate security controls
- Support AI and ML-powered products where data quality directly affects model outputs
- Mentor other engineers as the data function develops
- Contribute to longer-term technical direction and data architecture
Essential requirements
- Strong Python engineering skills with proven experience building and maintaining production data pipelines
- Experience designing and operating production-grade ETL or ELT systems
- Experience supporting AI or ML-powered products in production
- Strong understanding of data modelling and backend engineering principles
- Practical or conceptual understanding of graph databases and vector stores
- Experience working with cloud platforms, ideally Google Cloud Platform
- Familiarity with DevOps, infrastructure as code, CI/CD and cloud security controls such as identity and access management and secrets management
- Ability to take ownership of technically ambiguous problems and drive them through to production
- Strong communication skills and confidence working within a small, distributed engineering team
- Existing UK or EU work authorisation without requiring new visa sponsorship


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Nice-to-haves
- Experience within an early-stage B2B software company
- Experience with financial systems, including accounting, financial planning and analysis, billing or business analytics
- Experience with Snowflake, SQL, PostgreSQL or TypeScript
- Exposure to retrieval-augmented generation or graph-based retrieval architectures
- Interest in progressing towards technical leadership and mentoring responsibilities
Location and remote setup
This is a full-time, remote-first position for candidates based in London or Amsterdam, working primarily across UK and Central European time zones. The engineering team also works together in person periodically. Company-wide on-sites take place approximately every two months across London, Amsterdam or New York, so willingness to travel for these sessions is required.
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