About the Client

The Role

Responsibilities

• Lead technical delivery on Palantir Foundry/AIP engagements, from scoping through to production deployment
• Act as the senior technical point of contact for stakeholders, building trust and credibility at a senior level
• Design and build data pipelines, ontologies and applications using Python, PySpark and SQL
• Own architectural decisions and ensure technical quality across the engagement
• Mentor and support less senior engineers on the ground in Berlin
• Identify opportunities to expand scope and value within the engagement
• Contribute to internal best practice, tooling and delivery methodology

Essential Requirements

• Proven, lead-level experience delivering on Palantir Foundry and/or AIP
• Strong hands-on skills in Python, PySpark and SQL
• A track record of senior, client-facing delivery - comfortable owning the relationship, not just the code
• Experience leading or mentoring within a technical delivery team
• Ability to translate ambiguous business problems into clear technical solutions
• Strong communication and stakeholder management skills
• Eligibility to work in Germany, or willingness to be based in Berlin for the duration of the contract

Desirable Experience

• Experience within a Palantir partner consultancy or similar delivery-led environment
• Exposure to a broad range of Foundry modules (Ontology, Pipeline Builder, Contour, Workshop, AIP)
• Experience working with real-time data, event detection or risk/security platforms
• Experience contributing to proposals, scoping or pre-sales technical input

Working Environment

• Analyse large, complex, multi-source datasets in SQL and turn the results into clear, usable findings.
• Build and maintain dashboards and data visualisations in Tableau or Power BI that business and technical teams actually use.
• Assess, validate and improve data quality across the programme’s datasets.
• Support the supervisory intelligence, risk analytics and reporting that feeds regulatory decision-making.
• Work directly with business and technical stakeholders, translating between the two and keeping the analysis grounded in what they need.

• Strong SQL and hands-on experience analysing large-scale data across complex, multi-source datasets.
• Experience with AWS data services, particularly S3, DynamoDB and Athena.
• Dashboarding and data visualisation in Tableau or Power BI.
• Data quality assessment, validation and improvement.
• Genuine stakeholder skills across business and technical audiences, and the ability to explain technical work in plain English.
• A consulting mindset: delivery-focused, self-managing and credible in front of a client.

• Financial services, regulatory or public-sector delivery experience.
• Experience applying data quality or governance frameworks in a regulated environment.

• Test the pipeline, not the page. Own quality across large-scale Kafka streaming and batch data pipelines: ingestion, transformation, reconciliation and output.
• Build the test harnesses. Work directly alongside the data engineers to design and build the harnesses that make this system testable at scale. This is a build role as much as a test role.
• Prove it at volume. Prove correctness, completeness and integrity across volumes where sampling and eyeballing stop working and you need a genuine strategy.
• Build the CI safety net. Design and build the automated regression suite that runs on every release and proves accuracy, stability and response times have not moved.
• Own the strategy. Write the test strategy for this programme. There is a blank page here and the client wants someone who has an opinion about what goes on it.
• Own the assurance evidence. Prepare and complete formal test documentation for defence factory assurance: what was tested, how, against which criteria, signed off at each milestone.
• Muck in. This is a small, multidisciplinary team in a scaling business. Everyone gets hands on, including the engineering leadership.

• 1. Hands-on Kafka. Topics, partitions, consumer groups, offsets, replay, schema registry. Streaming is the architecture of this programme, not an adjacent interest.
• 2. Testing high-volume ETL or ELT data pipelines. Millions of rows a day and upward, in a system real users depended on, and you can explain how you did it rather than which tools you held.
• 3. Writing the test strategy. There is nothing in place on this programme yet. They want someone with a clear view of what to test first, where the risk sits in streaming data, and how to sequence and evidence it.
• 4. Modern architecture. REST, contract testing, schema validation. This is a greenfield build and legacy-only API experience will not translate.

• Automated regression testing in CI: repeatable suites that run on every release and check accuracy, stability and response times. Not one-off manual runs over chunked data.
• Comfort working close to data engineers, in the pipeline itself rather than at the UI layer, and building the tooling that makes testing possible.
• Python and SQL, and a structured, evidence-led approach: defined criteria, traceability, and the discipline to document what you did and why.
• Someone who can operate in a small team where the boundaries are loose and the standard is high.
• SC clearance, or genuine eligibility for it. Active clearance is strongly preferred on contract. See the note below, because this catches people out.

• How you tested a pipeline, not just that you did. Which technologies, how you handled schema and schema changes, and how you proved it held at volume. Naming tools is not the same as describing an approach.
• What runs in your CI when a release goes in. Splitting a large load into chunks and working through it is data processing. What matters here is the automated suite that catches a regression in accuracy or response time the moment a new release lands.
• How you would build the test strategy here. What you would test first, what the risks are in streaming data, how you would sequence it and how you would evidence it.
• What your frameworks buy this programme in speed and confidence, rather than a list of what you have used.

• SC clearance is required. Active clearance is strongly preferred on a contract engagement, though for the right person eligibility will be considered.
• Please read this carefully. Eligibility means a provable five-year UK address history. If you have lived outside the UK within the last five years, this will be difficult on this programme's timeline.
• A DBS check and BPSS clearance are not the same as SC. If that is what you hold, you are not yet cleared for this work.

• Remote across the UK. The client operates from multiple UK sites and hires nationally, so remote is the norm rather than the exception on this team.
• Occasional travel to a client site may be required, but this is not a requirement of the role day to day.

• Around £550 per day, negotiable. The client is open on rate for someone who genuinely has the Kafka and pipeline testing background.
• Two contract seats available on the programme.

• Building and maintaining features top to bottom: Python back end services and APIs, React and TypeScript on the front.
• Getting software into secure, air-gapped and sensitive environments, which means on-site deployment, integration and troubleshooting.
• Owning features properly. Scope it with the technical lead, CTO and customer, build it, test it, ship it, then support it.
• Containerising services and shaping how the platform runs on Kubernetes and bare-metal Linux.
• Writing code you would be happy to inherit, and holding that same line in review.
• Fixing production problems calmly, usually with less tooling than you would like and someone waiting on you.
• Working alongside the data, AI and platform engineers so models, pipelines and infrastructure land as one product rather than three.
• Improving the day to day: CI/CD, observability, security hardening, documentation.
• Sitting in front of customers and partners and turning what they need into something buildable.

• Python. Serious commercial experience building back end services, APIs and tooling. FastAPI, Django, Flask, whichever you have used in anger.
• TypeScript. Serious commercial experience on modern front ends with React, Vue or Angular.
• Linux. Properly comfortable without a GUI: shell, networking, processes, permissions, systemd, packages, and working out why a host is misbehaving.
• Full stack delivery. A track record of shipping whole features from database to browser, relational databases and SQL included.
• Containers and CI/CD. Docker plus automated build, test and deploy pipelines.
• Composure. You have delivered against customer deadlines that do not slip, and you get methodical rather than frantic when something breaks.
• Secure environment fit. Happy following strict security and handling procedures, and getting to UK customer sites when the programme needs you there.
• Communication. Clear with engineers and with customers who are not engineers.
• Clearance. Current, active SC. You must be UK based and able to hold and maintain UK clearance.

• Delivery into defence, national security or another heavily regulated sector.
• Running software in air-gapped or disconnected environments, including offline dependencies and moving artefacts across the boundary.
• Good instincts on secure development, authentication, authorisation and secrets management.
• Putting AI or ML models into production, LLM features included.
• Infrastructure as code with Terraform, Ansible or similar, plus configuration management.
• Observability and incident response: metrics, logging, tracing.
• Message queues, event-driven architectures or data pipelines.

• Kubernetes. Deploying, running or debugging workloads, including K3s, RKE2 or OpenShift.
• Data at scale. Spark, Trino, Parquet, Iceberg or similar columnar and distributed query tooling.
• GPU workloads and serving models on-premise.
• Open source contributions or a portfolio worth a look.
• Mentoring engineers or leading a small delivery team.
• DV clearance, or eligibility for it.

About the Client

The Role

Responsibilities

• Develop and maintain a Python codebase and database responsible for ingesting, cleaning, validating and reconciling data from internal and third-party sources
• Build REST APIs to serve as the bedrock of an internal platform
• Investigate inconsistencies in existing internal data, write validation rules and document definitions, and help establish trusted datasets for asset management
• Turn manual collection, checking, reconciliation, reminders, document generation and reporting tasks into dependable workflows
• Create dashboards, reports, alerts and small internal tools for investment, asset management, finance and operations functions
• Develop document extraction, retrieval and LLM-based workflows, including testing, evals and human-in-the-loop review mechanisms
• Write clean, tested, high-quality code; use version control; monitor jobs; investigate failures; and maintain clear technical documentation

Essential Requirements

• A rigorous degree in Computer Science, Data Science, Engineering, Mathematics or a closely related discipline
• Strong programming fundamentals in Python, TypeScript and SQL, demonstrated through useful software, research, internships, open-source work or a strong personal portfolio
• Understanding of and experience with relational databases, data modelling, APIs and ETL/ELT pipelines, with an enthusiasm to deepen these skills
• Care for readable code, testing, debugging, version control, and the difference between a promising prototype and a reliable production system
• The patience to trace messy data through unfamiliar systems, identify root causes and verify that a solution works
• A commercially minded, out-of-the-box thinker with an appetite to build and scale a platform
• Strong professionalism and maturity
• The ability to ask good questions, document decisions and explain technical issues to colleagues who do not write code
• A grounded, collaborative and high-agency approach – willing to seek guidance, act on feedback, and take on increasing responsibility as capability grows

Desirable Experience

• Internship, placement, research or project experience involving data pipelines, backend engineering, analytics engineering or automation
• Familiarity with a cloud platform for application deployment, Docker, data warehouses, business-intelligence tools, or simple internal web applications
• Practical exposure to LLM APIs, retrieval, evaluation, OCR or document-processing workflows
• Interest in real estate, finance, accounting, asset management, construction or how operational businesses actually use data
• Evidence of going beyond the teaching syllabus – a tool, service, open-source contribution, technical article or project used by someone other than you

Working Environment

About the Client

The Role

Responsibilities

• Set the technical direction and architecture for the organisation's internal data platform
• Design and build the core Python codebase and database responsible for ingesting, cleaning, validating and reconciling data from internal and third-party sources
• Design and build REST APIs to serve as the bedrock of the internal platform
• Establish trusted datasets for asset management, defining validation rules and data definitions
• Turn manual collection, checking, reconciliation, reminders, document generation and reporting into dependable, automated workflows
• Oversee the development of dashboards, reports, alerts and internal tools across investment, asset management, finance and operations functions
• Guide the development of document extraction, retrieval and LLM-based workflows, including testing, evals and human-in-the-loop review
• Support and mentor a Junior Data Engineer, setting standards for code quality, testing and documentation

Essential Requirements

• Proven, senior-level experience designing and building data platforms and architecture from the ground up
• Strong programming fundamentals in Python, TypeScript and SQL
• Deep experience with relational databases, data modelling, APIs and ETL/ELT pipelines
• A track record of taking systems from prototype to reliable production use
• The patience to trace messy data through unfamiliar systems, identify root causes and verify that a solution works
• A commercially minded, out-of-the-box thinker with an appetite to build and scale a platform
• The ability to explain technical decisions clearly to colleagues who do not write code
• Experience mentoring or supporting more junior engineers

Desirable Experience

• Experience with cloud platforms, Docker, data warehouses or business-intelligence tools
• Practical exposure to LLM APIs, retrieval, evaluation, OCR or document-processing workflows
• Interest in real estate, finance, accounting, asset management, construction or how operational businesses actually use data
• Evidence of having built and scaled a data platform or product from an early stage

Working Environment

About the Client

The Role

Responsibilities

• Contribute to technical delivery on Palantir Foundry/AIP engagements, from build through to production deployment
• Work directly with client teams to understand requirements and translate them into technical solutions
• Build data pipelines, ontologies and applications using Python, PySpark and SQL
• Support the design and implementation of architectural decisions set by senior engineers
• Test, validate and iterate on solutions against real client data and workflows
• Document technical decisions and contribute to internal best practice
• Build confidence and credibility with client stakeholders over the course of an engagement

Essential Requirements

• Hands-on experience delivering on Palantir Foundry and/or AIP
• Strong working skills in Python, PySpark and SQL
• Comfortable working directly with client stakeholders, not just internal teams
• Ability to translate business problems into clear technical solutions
• Good communication skills and a strong ownership mindset
• Eligibility to work in the UK, or requirement for visa sponsorship

Desirable Experience

• Experience within a Palantir partner consultancy or similar delivery-led environment
• Exposure to a broad range of Foundry modules (Ontology, Pipeline Builder, Contour, Workshop, AIP)
• Prior experience across a range of sectors and client types
• Interest in progressing toward more senior, lead-level delivery responsibility

Working Environment

About the Client

The Role

Responsibilities

• Lead technical delivery on Palantir Foundry/AIP engagements, from scoping through to production deployment
• Act as the senior technical point of contact for client stakeholders, building trust and credibility at a senior level
• Design and build data pipelines, ontologies and applications using Python, PySpark and SQL
• Own architectural decisions and ensure technical quality across engagements
• Mentor and support less senior engineers, contributing to the team's technical growth
• Identify opportunities to expand scope and value within existing client engagements
• Contribute to internal best practice, tooling and delivery methodology

Essential Requirements

• Proven, lead-level experience delivering on Palantir Foundry and/or AIP
• Strong hands-on skills in Python, PySpark and SQL
• A track record of senior, client-facing delivery - comfortable owning the relationship, not just the code
• Experience leading or mentoring within a technical delivery team
• Ability to translate ambiguous business problems into clear technical solutions
• Strong communication and stakeholder management skills
• Eligibility to work in the UK, or requirement for visa sponsorship

Desirable Experience

• Experience within a Palantir partner consultancy or similar delivery-led environment
• Exposure to a broad range of Foundry modules (Ontology, Pipeline Builder, Contour, Workshop, AIP)
• Prior experience across a range of sectors and client types
• Experience contributing to proposals, scoping or pre-sales technical input

Working Environment

• Partner with customers to understand operational challenges and success criteria
• Translate open-ended problems into clear technical designs and implementations
• Build AI agents that integrate with customer systems and perform real tasks
• Own deployments, including reliability, performance, and continuous improvement
• Test with real data, measure outcomes, and iterate based on results
• Collaborate with Product and Engineering to ship high-quality solutions
• Contribute to tools, documentation, and best practices that scale customer deployment

• 3+ years of experience in technical problem-solving roles
• Experience leading or contributing to solution scoping, discovery workshops, or early-stage AI/technical strategy
• Strong fundamentals in software design and system design
• Clear communication skills and a strong ownership mindset
• High-agency - comfortable creating clarity, proposing direction, and driving decisions without perfect requirements
• Experience working across systems, integrations, and data flows
• Comfort working directly with customers and owning ambiguous problems
• Genuine curiosity about building AI-powered systems that work in practice

• Experience in forward-deployed, solutions engineering, or customer-facing technical roles
• Exposure to AI agents, automation, or conversational systems
• Experience operating and improving production systems
• Bachelor's degree in Computer Science or a related technical field, or equivalent experience

• Partner with customers to understand operational challenges and success criteria
• Translate open-ended problems into clear technical designs and implementations
• Build AI agents that integrate with customer systems and perform real tasks
• Own deployments, including reliability, performance, and continuous improvement
• Test with real data, measure outcomes, and iterate based on results
• Collaborate with Product and Engineering to ship high-quality solutions
• Contribute to tools, documentation, and best practices that scale customer deployment

• 3+ years of experience in technical problem-solving roles
• Experience leading or contributing to solution scoping, discovery workshops, or early-stage AI/technical strategy
• Strong fundamentals in software design and system design
• Clear communication skills and a strong ownership mindset
• High-agency - comfortable creating clarity, proposing direction, and driving decisions without perfect requirements
• Experience working across systems, integrations, and data flows
• Comfort working directly with customers and owning ambiguous problems
• Genuine curiosity about building AI-powered systems that work in practice

• Experience in forward-deployed, solutions engineering, or customer-facing technical roles
• Exposure to AI agents, automation, or conversational systems
• Experience operating and improving production systems
• Bachelor's degree in Computer Science or a related technical field, or equivalent experience