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

Apply Now

Forward Deployed Data Engineer - AI Deployment Program

Planhat
London
1 month ago
Create job alert

Team

Planhat is a global leader in Customer Management solutions and we've been building toward our AI Platform (AIP) for some time and now.

As part of this journey, we've recently launched a new initiative to guarantee its efficacy: the AI Deployment Program (ADP)-a dedicated services team with deep expertise in deploying CX-enhancing AI capabilities, powered by the Planhat platform.

Mission

AI is only as powerful as the data it's trained on. At Planhat, our platform powers some of the most valuable customer data in the world-but unlocking its full potential requires strong engineering.

We're looking for Forward Deployed AI-focused Data Engineers to design, build, and optimize the data pipelines that power our AI Workflows, AI Automations, and customer operations.

This isn't a backroom ETL role-you'll work directly with our Forward Deployed Solutions team and strategic customers to transform messy, complex datasets into clean, structured, and reliable fuel for AI models.

You'll own the process from end to end: embedding with customers to understand their systems, engineering pipelines that deliver at scale, and working closely with our commercial teams to build workflows and solutions that our customers are asking for.

Role

  • Architect and implement high-performance data pipelines for AI applications.
  • Design and optimize and transform raw customer data into structured, reliable datasets.
  • Build AI workflows and data mapping in the Planhat platform
  • Work with SQL, Python, and APIs to integrate multiple, messy, distributed systems.
  • Partner with AI engineers to ensure models have the clean, context-rich data they need.
  • Build monitoring and validation systems to ensure data quality and trust.
  • Collaborate with customers and internal teams to solve complex, domain-specific data challenges

Advantages

You'll:

  • work at the intersection of AI, customer data, and real-world outcomes.
  • get to solve complex data problems for some of the world's most innovative companies.
  • be part of a small, high-caliber team with the autonomy to design and own your work end-to-end.
  • 5+ years experience in data engineering, ideally in B2B or AI-focused environments.
  • Strong expertise in SQL, data modeling, and ETL/ELT tools.
  • Proficiency with Python or similar scripting languages.
  • Experience integrating with REST/GraphQL APIs and building data ingestion frameworks.
  • Understanding of data quality, governance, and observability best practices.
  • Experience with ML pipelines, vector databases, or RAG architectures.
  • Willingness to travel to customer sites as needed.


#J-18808-Ljbffr

Related Jobs

View all jobs

Forward Deployed Data Engineer - AI Deployment Program

Forward Deployed Data Scientist

Principal Data Scientist

Data Scientist - Placement Year

Data Scientist - Decisioning (Pega)

Senior Data Architect

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.

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.

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.

Why the UK Could Be the World’s Next Data Science Jobs Hub

Data science is arguably the most transformative technological field of the 21st century. From powering artificial intelligence algorithms to enabling complex business decisions, data science is essential across sectors. As organisations leverage data more rapidly—from retailers predicting customer behaviour to health providers diagnosing conditions—demand for proficiency in data science continues to surge. The United Kingdom is particularly well-positioned to become a global data science jobs hub. With world-class universities, a strong tech sector, growing AI infrastructure, and supportive policy environments, the UK is poised for growth. This article delves into why the UK could emerge as a leading destination for data science careers, explores the job market’s current state, outlines future opportunities, highlights challenges, and charts what must happen to realise this vision.