Staff Forward Deployed Engineer

Manchester Engineering – Software Development /Full time /Remote Are you ready to shape the future of data?

Matillion is the company behind Maia, the AI Data Automation platform. In the AI economy, demand for data is exploding. Manual data engineering can’t keep up. Maia fixes that by combining 15 years of data expertise with agentic AI to eliminate the manual work that slows data teams down. Organisations like Cisco, Docu Sign, and Slack are already using it to deliver real business impact, faster.

We started in Manchester and now we’re global - with teams across the UK, US and India.

We are driven, curious, energetic people who move fast, think big and hold ourselves to a high standard. We’re here to make a dent in the universe bigger than ourselves. And we’re looking for people who want to be part of it.

The Staff Forward Deployed Engineer is the senior operator we put on our most significant and complex Maia rollouts and expansions. Working primarily remotely with our distributed teams and on-site when it counts, they own these engagements end to end, architecting and building production-grade solutions, modifying Matillion’s own product code where the platform needs it, and holding the highest engineering bar under real delivery pressure.

A true force multiplier, they work at every level and across Sales, Product, Engineering, and Customer Success: earning technical wins, acting as a hands-on escalation point to Customer Success, and driving adoption and expansion in their accounts. They ship quickly and to standard in a low-friction way, turn their work into reusable assets and product feedback, and mentor the FDEs coming up behind them.

What you will be doing:

Owning end-to-end customer engagements by running discovery, architecting multi-cloud deployments, writing production-grade code, and guiding projects through to production cut-over.

Building complex data pipelines, models, and integrations across cloud data platforms to ensure customers achieve the core outcomes they adopted Maia for.

Modifying Matillion’s underlying codebase directly when native platform features are missing, adhering to strict engineering, security, and quality standards.

Delivering fast, pragmatic MVPs by diagnosing real underlying customer problems, questioning initial requirements, and shrinking scope to accelerate platform adoption.

Cultivating executive trust and serving as a cross-functional catalyst across Sales, Product, Engineering, and Customer Success to resolve complex escalations at the first point of contact.

Enabling total customer self-sufficiency by training internal champions and creating clear handover documentation for Customer Success and Support teams upon project exit.

Securing technical wins during pre-sales cycles through technical discovery, proof-of-concept deliveries, objection handling, and joint strategy work with Account Executives.

Influencing product evolution by identifying repeating delivery patterns, submitting structured product feedback, and building reusable implementation frameworks that minimize future custom work.

Working agentic-first by integrating AI tools across the entire delivery lifecycle while setting clear quality validation standards for AI-generated outputs.

Elevating team performance by mentoring junior engineers, shaping hiring standards, refining delivery processes, and continuously updating expertise in emerging AI and cloud tech.

What we are looking for: 5+ years of experience in production-grade software development and data integration, featuring expert Python, SQL, and object-oriented skills (Java/Go) for designing reusable architectures and refactoring complex codebases.

Deep knowledge of distributed systems, data architecture, CI/CD, Kubernetes, secure enterprise networking, and at least one major cloud provider (AWS, Azure, or GCP).Hands-on expertise in scalable data pipelines and cloud data platforms like Snowflake, Databricks, Redshift, or Big Query, alongside familiarity with the broader Matillion product estate.

Disciplined use of AI tools across the delivery process with the ability to validate output, supported by optional experience in production LLMs,…