Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior/Lead Data Engineer

Recursion Agentic AI
9 months ago
Applications closed

Related Jobs

View all jobs

Senior Lead Data Engineer

(Senior) Lead Data Engineer in Staines-upon-Thames - IFS

Senior Data Engineer

Principal Geospatial Data Engineer

Lead Snowflake Data Engineer

Lead/Senior Data Scientist

Who we Are

Recursion is an institutionally-backed startup currently in beta mode that is redefining business intelligence and automation with agentic AI. Our mission is to deliver non-obvious insights tailored specifically to each business and to automate complex processes beyond the capabilities of traditional RPA tools. By consolidating all data into a single source of truth and making it accessible in real-time via natural language conversations, we empower enterprises to make quick, confident decisions without delays in data processing or preparation. 


About the Role

The Data Engineer will design and maintain ETL pipelines for our clients, ensuring efficient ingestion, transformation, and storage of data. This person will play a key role in transforming various client’s data in the format most suitable for AI agents.


Key Responsibilities:

  • Design, develop, and maintain scalable ETL pipelines to ingest, transform, and store data tailored to individual client requirements.
  • Implement efficient data processing workflows for structured and unstructured data.
  • Develop processes for raw data ingestion, transformation, and storage.
  • Automate the generation of master data views on a regular basis.
  • Collaborate with data analysts and app development teams for seamless data flow.
  • Monitor and optimize data pipeline performance.


Qualifications:

  • A minimum of 5 years of experience in a professional data engineering role.
  • Expertise in ETL tools and frameworks (e.g., Apache Airflow, AWS Glue).
  • Proficiency in Python, SQL, and cloud services (AWS, GCP, or Azure).
  • Familiarity with data warehousing and transformation techniques.
  • Strong debugging and performance optimization skills.
  • Experience with real-time data processing frameworks.
  • Knowledge of machine learning pipelines and integration.
  • Familiarity with data visualization tools (e.g., Tableau, Looker, or Power BI).
  • Background in working with APIs and integrating external data sources.
  • Ownership: Track record of driving and delivering complete, high quality solutions to problems independently.
  • Experience mentoring junior team members.


How to Apply

Please submit your resume and a brief cover letter explaining your interest in the role and how your experience aligns with the responsibilities and qualifications.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Jobs

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Jobs

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.