Senior Data Engineer (AI & Data Products)

Posted 3 Hours Ago
Be an Early Applicant
2 Locations
Remote
90K-110K Annually
Senior level
Professional Services • Consulting
The Role
Own production Python data pipelines, ETL/ELT workflows, and the ontology powering an AI platform. Integrate warehouses and business applications with graph databases and vector stores, while managing deployment tooling, cloud infrastructure, monitoring, and security. The role begins as hands-on individual contribution and develops toward technical leadership through mentoring and architecture ownership.
Summary Generated by Built In

About the company

Our client is an early-stage AI company building agents for finance teams and the Office of the CFO. Its platform connects financial data across systems so AI can retrieve information and reason accurately across complex business entities.

The role / why it matters

As a Senior Data Engineer, you will own production data pipelines and the ontology behind an AI platform, reporting directly to the CTO. You will stay hands-on while growing toward technical leadership in a small, remote-first team.

What you'll do

• Build and operate Python ingestion pipelines into graph databases and vector stores.

• Integrate data warehouses and business applications into reliable ETL/ELT workflows.

• Design the data ontology for accurate retrieval and agent reasoning.

• Own deployment tooling, cloud infrastructure, monitoring and security.

• Progress from primarily individual contribution toward a 60/40 split of engineering and mentoring or architecture leadership.


Requirements

What we're looking for

• 6-10 years of professional data engineering experience.

• Strong production Python skills and ownership of reliable ETL/ELT pipelines.

• Experience supporting AI or machine learning features in production.

• Conceptual or hands-on knowledge of graph databases and vector stores, beyond a SQL-only background.

• Cloud platform experience, preferably GCP, plus infrastructure as code, CI/CD and cloud security.

• Existing authorization to work in the UK or EU.

• Ability to work UK/CET hours and attend team on-sites about every two months.

Bonus points

• Early or founding engineering experience at a B2B startup.

• Financial systems, accounting, FP&A or business analytics experience.

• Interest in growing into a technical team lead.


Benefits

Compensation and benefits

• £90,000-£110,000 annual base salary plus competitive equity.

• Direct ownership of data architecture and a path toward team leadership.

Location / work model

Full-time, remote-first, based in Amsterdam (preferred) or London and working UK/CET hours. The team may co-work locally and meets onsite about every two months in New York, London or Amsterdam. Existing UK or EU work authorization is required; new visa sponsorship is not available.

Skills Required

  • 6–10 years of professional data engineering experience
  • Strong production Python skills
  • Experience owning reliable ETL/ELT pipelines
  • Experience supporting AI or machine learning features in production
  • Conceptual or hands-on knowledge of graph databases and vector stores
  • Cloud platform experience, preferably GCP
  • Experience with infrastructure as code, CI/CD, and cloud security
  • Existing authorization to work in the UK or EU
  • Ability to work UK/CET hours
  • Ability to attend team on-sites about every two months
  • Early or founding engineering experience at a B2B startup
  • Financial systems, accounting, FP&A, or business analytics experience
  • Interest in growing into a technical team lead
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The Company
28 Employees
Year Founded: 2021

What We Do

Raydar is a talent acquisition and business consulting firm that connects world-class and emerging talent with growing organizations. It supports companies through team development, strategic hiring, and customized growth solutions, helping clients recruit roles such as engineers, product managers, executives, legal counsel, and quantitative traders. Raydar focuses on understanding each organization’s needs, culture, and long-term goals to build high-impact teams.

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