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Matillion

AI-powered data pipeline management platform

Staff Forward Deployed Engineer

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeManchester, UKRemote

About the Job

Requirements

  • At least 5 years of experience in production-grade software development and data integration, with expert Python, SQL, and object-oriented skills in Java or Go for designing reusable architectures and refactoring complex codebases.
  • Deep knowledge of distributed systems, data architecture, continuous integration and continuous delivery, 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 such as Snowflake, Databricks, Redshift, or BigQuery, alongside familiarity with the broader Matillion product estate.
  • Disciplined use of AI tools across the delivery process and ability to validate AI-generated output.
  • Proven background in customer-facing technical delivery, including pre-sales technical discovery, hands-on implementation, and escalation management.
  • Strong engineering judgment and systems thinking to make architectural trade-offs between speed, scalability, and maintainability under ambiguity.
  • High autonomy to deliver working production systems independently in high-pressure environments.
  • Customer empathy and rapport-building capabilities to establish trust with technical teams and executive stakeholders.
  • Ownership of outcomes and a multiplier mindset to elevate surrounding team members.

Responsibilities

  • Own end-to-end customer engagements by running discovery, architecting multi-cloud deployments, writing production-grade code, and guiding projects through production cut-over.
  • Build complex data pipelines, models, and integrations across cloud data platforms to ensure customers achieve the outcomes for which they adopted Maia.
  • Modify Matillion’s underlying codebase directly when native platform features are missing, adhering to engineering, security, and quality standards.
  • Deliver pragmatic MVPs by diagnosing underlying customer problems, questioning initial requirements, and narrowing scope to accelerate platform adoption.
  • Cultivate executive trust and serve as a cross-functional catalyst across Sales, Product, Engineering, and Customer Success to resolve complex escalations at the first point of contact.
  • Train internal champions and create handover documentation for Customer Success and Support teams to enable customer self-sufficiency upon project exit.
  • Secure technical wins during pre-sales cycles through technical discovery, proof-of-concept deliveries, objection handling, and joint strategy work with Account Executives.
  • Influence product evolution by identifying recurring delivery patterns, submitting structured product feedback, and building reusable implementation frameworks that minimize future custom work.
  • Integrate AI tools across the delivery lifecycle and set quality validation standards for AI-generated outputs.
  • Mentor junior engineers, shape hiring standards, refine delivery processes, and update expertise in emerging AI and cloud technology.

Desired Qualifications

  • Experience in production large language models, retrieval-augmented generation, and AI agents.

About the Company

Matillion

AI-powered data pipeline management platform

Matillion builds a data management platform that helps data teams build, manage, and orchestrate data pipelines. The platform supports moving, transforming, and orchestrating data from many sources using a library of hundreds of connectors, with both no-code and code-based options (SQL, Python, dbt). AI features integrate large language models into pipelines and automatically generate documentation to boost data literacy. Pricing is usage-based, so clients pay for what they use, enabling easy scaling as needs grow. Matillion differentiates itself by its AI-enabled pipeline automation, a unified view that covers no-code to code workflows, and a broad connector ecosystem. The company aims to boost data team productivity by making data pipelines faster to build and easier to manage, while improving data literacy across the organization.

Company size
201-500
Company stage
Series E
Total funding
$309.4M
Headquarters
Salford, United Kingdom
Founded
2010

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