Jobgether
Senior AI-First Data Engineer

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Job Title: Senior AI-First Data Engineer
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior AI-First Data Engineer based in United Kingdom.
This role offers the opportunity to shape the future of data engineering within an AI-driven environment. You will help build a next-generation cloud data platform designed to make business data accessible, intelligent, and actionable for both people and AI systems.
Working at the intersection of data engineering, automation, and artificial intelligence, you will create the foundations that power smarter decision-making and agent-driven workflows.
You will contribute to modernizing data architecture, moving from legacy systems toward scalable, streaming-first solutions. The position combines hands-on technical leadership, innovation, and collaboration across engineering, product, analytics, and business teams. You will play a key role in creating an AI-native data ecosystem within a fast-growing global technology environment.
Accountabilities:
- As a Senior AI-First Data Engineer, you will be responsible for designing, evolving, and scaling modern data infrastructure while enabling AI-powered business capabilities.
- Build and evolve a scalable, cloud-native data platform that supports AI applications, analytics, automation, and business operations.
- Lead the transition from traditional batch processing architectures toward near real-time and streaming data systems.
- Improve data platform reliability, observability, governance, security, and performance through engineering best practices.
- Develop data products and foundations that allow AI agents, analytics systems, and business users to access and leverage trusted information.
- Create semantic layers, metadata structures, and knowledge frameworks that make data more discoverable and actionable.
- Enable AI-driven reporting, forecasting, and business intelligence capabilities by transforming static analytics into dynamic operational systems.
- Use AI tools to accelerate engineering workflows, including development, testing, documentation, debugging, and monitoring.
- Design systems that allow AI agents to safely query, understand, and interact with business data.
- Evaluate emerging AI technologies and identify opportunities to improve productivity across data teams.
- Improve accessibility and adoption of BI solutions while maintaining strong governance and data quality standards.
- Provide technical leadership through architecture guidance, code reviews, mentorship, and knowledge sharing.
- Partner with engineering, product, analytics, and business stakeholders to align technical investments with strategic goals.
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:
- The ideal candidate is an experienced data engineering professional with a strong background in building scalable platforms and applying AI-driven approaches to modern data workflows.
- 6+ years of experience in data engineering, analytics engineering, or a related technical field.
- Proven experience designing, implementing, and operating modern cloud-based data platforms.
- Experience working in high-growth SaaS or technology environments.
- Strong ability to manage complex projects from technical design through successful delivery.
- Experience collaborating with both technical teams and business stakeholders.
- Hands-on expertise with Databricks, dbt, Airflow, Python for data engineering, SQL, and data modeling.
- Strong understanding of data warehousing architectures, orchestration, integration, quality frameworks, and governance practices.
- Experience with streaming architectures, event-driven systems, BI platforms, product analytics tools, CRM data platforms, or customer data platforms.
- Demonstrated AI-first mindset, including experience using AI-powered development workflows and automation tools.
- Ability to leverage AI for debugging, testing, documentation, architecture exploration, and productivity improvements.
- Curiosity about agentic systems and experience integrating AI into data or analytics workflows.
- Nice-to-have experience with AI-native data products, semantic layers, RAG systems, vector databases, knowledge graphs, or enabling AI agents to consume operational data.


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Benefits:
- Remote-friendly working environment with flexibility to work from locations where you perform best.
- Opportunity to join a globally distributed team across multiple countries and cultures.
- Chance to contribute to the development of an AI-native organization and shape the future of workplace technology.
- Exposure to cutting-edge AI, automation, and data engineering initiatives.
- High-impact role within a fast-growing technology company scaling globally.
- Collaborative culture focused on ownership, innovation, transparency, and continuous learning.
- Opportunities for professional growth while working on complex technical challenges.
- Ability to influence technical strategy and build foundational systems with long-term impact.
- Inclusive workplace that values diverse perspectives and encourages everyone to contribute.
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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