Wiz CNAPP Implementation Consultant (Freelance) <ul><li>Contract: Freelance, 12 months</li><li>Location: Remote, UK-based</li><li>Day rate: Competitive </li><li>IR35: Inside</li><li>Client: Global medical device manufacturer (FTSE 100)</li></ul>The opportunity A FTSE 100 global medical technology manufacturer has selected Wiz as its CNAPP platform after an enterprise evaluation. They now need an experienced consultant to take it from selection to a stable, fully operational BAU capability. This is a hands-on, end-to-end role within a wider cloud security programme. That programme supports cloud adoption, AI, SaaS, data platforms and M&A integration across a large, regulated enterprise. You'll work alongside the client's security teams and Wiz Professional Services. What you'll deliver:<ul><li>Discovery and design: confirm the environment, licensing, prerequisites and integrations, then define the implementation design and sequence.</li><li>Infrastructure onboarding: onboard all in-scope AWS, Azure, GCP, Kubernetes and SaaS environments into Wiz, then validate discovery and coverage.</li><li>Integrations: connect Wiz to SIEM/SOC tooling, ticketing (e.g. ServiceNow, Jira), CI/CD and vulnerability management, and prove data flows end to end.</li><li>Configuration and tuning: build the policy baseline, risk prioritisation, ownership mapping, dashboards, reporting and exception handling.</li><li>Operationalisation: set up finding routing and operating procedures, run training and knowledge transfer, and provide hypercare into BAU.</li><li>Roadmap: recommend and prioritise next steps for coverage, controls, automation and measurable risk reduction.</li><li>Governance: keep clear implementation records, report on progress and evidence acceptance against success criteria.</li></ul>What you'll bring Essential: <ul><li>Hands-on experience implementing Wiz end to end in a large enterprise: connectors, deployment, policy configuration and tuning.</li><li>Strong multi-cloud security knowledge across AWS, Azure and/or GCP, including IAM, networking and Kubernetes.</li><li>Experience integrating a CNAPP or CSPM platform with SIEM, ITSM (ServiceNow/Jira) and CI/CD pipelines.</li><li>A track record of taking a security platform into BAU: runbooks, ownership models, training and handover.</li><li>Confident with stakeholders, from engineering teams to security leadership, in a matrixed organisation.</li></ul>Desirable: <ul><li>Wiz certifications, or delivery experience with a Wiz partner or Wiz Professional Services.</li><li>Experience with other CNAPP tools (Prisma Cloud, Microsoft Defender for Cloud, Orca, Lacework).</li><li>Infrastructure-as-code (Terraform) and security automation.</li><li>Experience in regulated sectors such as medical devices, life sciences, pharma or financial services.</li></ul>

Wiz CNAPP Implementation Consultant (Freelance)

Lead AI Data Scientist

 

Build the data science function at a PE-backed legal services group going all-in on AI

 

Our client is a fast-growing, private equity-backed legal services group. They’ve grown through a successful buy-and-build strategy and now bring together several leading regional law firms across the UK.

 

They’ve just secured board approval to roll out a centralised AI platform across the whole group. AI adoption is already high (around 95% of lawyers use it), but use isn’t joined up across the firms. The next phase is making it structured, measurable and scalable. This is a newly created role to lead data science across that programme.

 

Why this role?

<ul>
	<li>Founding role: you’ll be the first data scientist and will hire, with room to grow the function from there.
	<li>Models that ship: this is a PE-backed business with a mandate to deliver, so your work goes into production rather than sitting in a notebook.
	<li>Real influence: you’ll be at the heart of the business, shaping how an entire group uses AI, not one of hundreds of data scientists.
	<li>Legal is ahead of the curve: it’s one of the few industries where AI has moved from experiment to everyday practice. What you do here will play out in other sectors later, and you’ll have done it first.
</ul>

 

What you’ll do

<ul>
	<li>Work with lawyers, subject matter experts, business analysts and engineers to find where AI and automation can have the biggest impact in legal workflows.
	<li>Prototype LLM-based solutions and test them using human-in-the-loop review and LLM-as-judge evaluation, then guide the successful ones into production.
	<li>Map data across matter, client, document, time-recording and billing systems, and help define a target data model.
	<li>Set baselines and success metrics, and build before-and-after analysis and dashboards to show impact on productivity, quality, cost and margin.
	<li>Monitor models and AI-enabled workflows in production for quality degradation and drift.
</ul>

 

What we’re looking for

<ul>
	<li>5+ years as a data scientist, including time leading or setting direction for DS work.
	<li>A track record of taking models from prototype into production and keeping them running.
	<li>Hands-on experience building and evaluating LLM solutions, including prompt design, RAG and structured evaluation. Exposure to agents, MCP or context engineering is a plus.
	<li>Strong Python and SQL, plus experience on a cloud data platform (Databricks, Azure or Snowflake).
	<li>Experience defining success metrics and showing measurable business impact.
	<li>Excellent stakeholder skills, with the ability to turn workflows into testable AI proposals and explain trade-offs to senior, non-technical audiences.
	<li>Experience mentoring or managing others, or a clear ambition to move into people leadership.
</ul>

 

Nice to have

<ul>
	<li>Professional services, legal or legal tech experience.
	<li>Background in a regulated, data-driven industry such as financial services or insurance.
	<li>PE-backed or investor-owned environment experience.
	<li>Familiarity with legal platforms (ShareDo, Clio, Aderant) or legal AI tools (Jylo, Lexis Protégé, Copilot).
	<li>Awareness of confidentiality, privilege and data-protection considerations when applying AI to client data.
</ul>

 

This is a full-time position with a hybrid set-up from their central London office. Unfortunately visa sponsorship and relocation support are not available for this role.

Lead AI Data Scientist

Senior Backend Developer (f/m/d)

Who we are looking for

As Senior Backend Developer (f/m/d), you will help us scale our platform to support business growth and further develop our product portfolio to the next level. You are driven by innovation and new ideas and enjoy working closely within an agile, cross-functional team ready for new approaches to software development.

<ul dir="ltr">
	<li>Further development of our software solutions to support business growth
	<li>Take responsibility for green-field projects in finance
	<li>Keep our services running and ensure stable operation
	<li>Work with a supportive IT team using agile methods, alongside colleagues in other departments (e.g. Product, Operations)
</ul>

Your skills

Must have

<ul dir="ltr">
	<li>Several years of professional experience
	<li>Passion for emerging (web) technologies
	<li>Strong testing habits (JUnit, Mockito, Cypress, etc.)
	<li>Broad experience with Java frameworks such as Spring, Hibernate
	<li>Experience designing relational databases, with practical experience in MySQL/PostgreSQL
	<li>Solid understanding of software paradigms and design principles (OOP/FP, MVC, Dependency Injection, Messaging)
</ul>

Extra credit for

<ul dir="ltr">
	<li>Bachelor’s or Master’s degree in Computer Science or a related field
	<li>Experience with ERP systems, particularly SAP FICO
	<li>Experience working in regulated environments
	<li>Proficiency in JavaScript/TypeScript and React
	<li>Experience with DevOps and process automation
	<li>Experience scaling web applications and databases
	<li>Knowledge of financial markets, auctions and corporate finance
</ul>

What we offer

<ul dir="ltr">
	<li>Impact: a diverse range of responsibilities in an innovative, modern fintech company, with plenty of room for initiative and personal development.
	<li>Cross-functional collaboration: engaging, cross-departmental projects that give you the opportunity to actively shape your role and work environment.
	<li>Continuous growth: regular, structured feedback meetings, individual training opportunities, and an annual development budget you manage independently.
	<li>Flexibility meets team spirit: flexible working hours to balance your professional and personal life, without losing close collaboration with the team.
	<li>Attractive and appreciative benefits: fair compensation based on experience, 30 days of annual leave, and a great office culture.
</ul>

About us

We are a growing fintech company that combines payment processing with financing solutions, helping businesses optimise cash flow and payment terms across their supply chains.

We work with established financing partners and a large, growing portfolio of client programs across a range of industries, delivering tailor-made solutions that strengthen liquidity and efficiency for our customers.

We are based in Germany and operate as a licensed, regulated financial services provider.

Senior Java Developer

Analytics Engineer

Location: London 
Working arrangement: Hybrid, 1-2 days per week in the office 
Salary: Up to £55,000 plus bonus

About the Business

An established technology business is looking for an Analytics Engineer to join its Data Platform team. Data sits at the heart of its customer experience, with teams across the business relying on trusted insights to improve products, understand customer behaviour and make better decisions.

The Opportunity

You’ll work at the intersection of data engineering and analytics, building scalable transformation pipelines and reliable data models that support reporting, experimentation and decision-making.

Working closely with Product, Marketing, Engineering, BI and Data Science, you’ll translate business requirements into accessible, well documented data products. Alongside delivering new models, you’ll help improve data quality, warehouse performance and the wider data platform.

Key Responsibilities

• Build, optimise and maintain data transformation pipelines using dbt and Snowflake. 
• Design reusable data models that support consistent, trusted reporting and analysis. 
• Improve the performance, security and cost efficiency of the Snowflake data warehouse. 
• Develop automated data quality tests, monitoring and alerting. 
• Collaborate with stakeholders across Product, Marketing, BI, Engineering and Data Science to deliver data products that meet business needs. 
• Maintain clear documentation and promote best practices in analytics engineering. 
• Contribute to platform improvements, including the evaluation and adoption of orchestration tools such as Dagster. 
• Ensure data products remain reliable, accessible and useful as business requirements evolve.

Skills and Experience

• Strong SQL skills, including experience writing and optimising complex queries. 
• Commercial experience using dbt to build and maintain data transformation pipelines. 
• Experience with Snowflake or another modern cloud data warehouse, such as BigQuery. 
• Experience building data models for analytics and reporting. 
• Familiarity with Python for automation, data manipulation or integration tasks. 
• An interest in improving data quality, reliability and performance. 
• Strong problem-solving skills and the ability to work in a collaborative environment. 
• Clear communication skills, with the ability to translate business requirements into technical solutions.

Technology Environment

The wider stack includes Snowflake, dbt, SQL, Python, Fivetran, Dagster, Metaplane and Tableau, alongside AWS, Terraform and GitHub.

You don’t need experience with every tool listed. Strong SQL, commercial dbt experience and relevant cloud data warehouse experience are the key requirements.

What’s on Offer

• Base salary of up to £55,000 plus bonus. 
• Hybrid working with 1-2 days per week in the Farringdon office. 
• The opportunity to influence data models, engineering practices and platform improvements. 
• Collaboration with teams across Product, Marketing, Engineering, BI and Data Science. 
• An environment that values continuous improvement, knowledge sharing and learning.

Apply to find out more, or contact Cameron Mason at Xcede for a confidential conversation.

Analytics Engineer

Matthew has specialised in the Tech and Data market since 2014, navigating key industry shifts from the rise of DevOps and Data Science to today’s AI boom. Focused on the Berlin and Hamburg markets, he has supported businesses at every stage of growth, from building founding teams to delivering strategic leadership hires. He is also active in the local tech community, hosting leadership dinners and TA brunches to connect and share insights.

Senior Java Developer

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Matthew Rees-Davis

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