Jobgether
Senior Data Engineer (AI-Native) — Data Layer

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Job Description: Senior Data Engineer (AI-Native) — Data Layer
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer (AI-Native) — Data Layer based in United Kingdom.
This role offers the opportunity to build and scale the core data infrastructure behind an AI-powered platform transforming a major global industry.
You will own the architecture, pipelines, and systems that ensure data is accurate, reliable, and ready to power intelligent products.
The position combines deep technical ownership with innovation, requiring both strong engineering fundamentals and an AI-native approach to development.
You will work on complex data challenges involving multiple sources, large-scale processing, and modern cloud technologies.
Your contributions will directly influence how businesses leverage data and AI to improve operational efficiency and decision-making.
This is an opportunity for an experienced engineer who thrives in a fast-moving environment and enjoys building foundational systems from the ground up.
Accountabilities:
- Own the Data Layer architecture, including ingestion pipelines, medallion-style data models, and serving layers.
- Design, build, and maintain reliable ingestion and transformation pipelines across various data sources.
- Integrate and reconcile complex real-world data from file-based systems, streaming events, and APIs.
- Develop data models across raw, refined, and curated layers to ensure data quality and accessibility.
- Build systems that guarantee data reliability through validation, reconciliation, lineage tracking, backfills, and incremental processing.
- Improve the scalability, performance, and tooling of the data platform as requirements evolve.
- Leverage AI-powered development tools to accelerate engineering workflows while maintaining high standards for code quality and reliability.
- Define and maintain data contracts in collaboration with backend, AI, product, and customer-facing teams.
- Troubleshoot complex data issues and ensure downstream systems and AI applications receive accurate information.
- Take ownership of projects from concept through production, making thoughtful decisions on architecture and implementation.
Reasons to use Rodeo
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?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
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.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
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.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Requirements:
- 7+ years of hands-on experience as a data engineer with proven ownership of production-scale data systems.
- Strong programming and SQL skills, with the ability to design efficient pipelines, schemas, and analytical models.
- Deep understanding of data engineering principles, including query optimization, debugging, and data correctness.
- Experience building reliable ingestion and ELT pipelines from complex and varied data sources.
- Hands-on experience with cloud data warehouses and major cloud platforms.
- Experience working with multiple data source types, including files, event streams, and APIs.
- Strong understanding of data consistency challenges such as partial loads, schema changes, late-arriving data, and idempotency.
- Experience using AI-assisted development tools such as Claude Code, Cursor, Codex, or similar solutions in daily engineering workflows.
- Ability to structure AI-assisted workflows, validate outputs, and apply strong engineering judgment.
- Strong ownership mindset with the ability to move quickly, prioritize effectively, and make pragmatic technical decisions.
- Excellent written and verbal communication skills, with the ability to explain technical concepts to both technical and non-technical stakeholders.
- English proficiency at C1 level or above.
Additional experience with the following is highly valued:
- Advanced experience with cloud data warehouses and modern data transformation frameworks.
- Streaming and event-driven data ingestion at scale.
- Medallion architecture or lakehouse implementations.
- Enterprise system integrations, including ERP or ecommerce platforms.
- Building data platforms that support AI/ML applications, retrieval systems, or model data pipelines.
- Previous experience in an early-stage SaaS or high-growth technology environment.


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Benefits:
- Fully remote work environment across Europe.
- Flexible working arrangements with meaningful overlap with international teams.
- Opportunity to build foundational AI-powered systems with significant business impact.
- High ownership role with autonomy to influence architecture and technical direction.
- Collaborative environment with experienced engineers, product teams, and AI specialists.
- Opportunity to work with modern cloud technologies and AI-native development tools.
- Professional growth opportunities in a fast-growing technology company.
How Jobgether Works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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