machine learning engineer

data scientist

data engineer

platform engineer

analytics engineer

data modeler

Ci&T

At CI&T, we help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions.
 
With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data & AI, Martech and Business strategy.
 
We are 8,000 CI&Ters across more than 25 countries, collaborating to build solutions with real impact. AI is already part of how we work, evolve, and innovate every day.
 
We're looking for a contractor to join us on a 6 month basis to help with a project in the financial services sector focussing on their DBT Modelling, cross-domain data products and trusted analytics-ready datasets.
 
In this role you'll: 
Build and maintain DBT models for cross-domain analytics use cases
 Create reusable facts, dimensions and marts for analytics consumption
 Support cross-domain data products such as Churn, LTV, Segmentation and Customer Intelligence
 Implement dbt tests, source freshness checks and reconciliation logic
 Translate business requirements into data models and metric logic
 Support data quality checks and model validation
 Document model definitions, business rules, assumptions and lineage
 Work closely with analytics and domain teams to ensure datasets are fit for reporting and decisioning
 
We need someone with these skills: 
Strong hands-on experience with DBT
 Strong SQL and Snowflake experience
 Experience building facts, dimensions, marts and analytics-ready data models
 Strong understanding of data modelling and metric design
 Experience implementing dbt tests, source freshness checks and data quality validations
 Ability to translate business requirements into trusted data models
 Experience working with analysts, product teams and business stakeholders
 Good documentation skills for model logic, metric definitions and lineage
 Experience working in modern data stack environments
 
Collaboration is our superpower, diversity unites us, and excellence is our standard.
 We value diverse identities and life experiences, fostering a diverse, inclusive, and safe work environment. We encourage applications from diverse and underrepresented groups to our job positions.

[29868] - Data Analytics Engineer - DBT Modelling (Contract)

JustPark

<div>About JustPark
JustPark is the premier partner offering both B2B solutions for destinations and B2C services for drivers, giving us the best of both worlds. We simplify the entire parking experience. From venues and councils to private driveways, our platform makes it simple for drivers to find, book, and pay for parking, while empowering our operating partners to deliver exceptional parking experiences.
We've always believed parking should be easier, from end to end. That's why we, two trailblazing companies - ParkHub and JustPark - have come together to make that vision a reality.
ParkHub revolutionized event parking in the US, optimizing venue operations for a smoother, stress-free experience. JustPark transformed parking in the UK, turning the hunt for a spot into a simple, seamless task.
Now, as one unified company, we're combining expertise to offer a full-service, frictionless parking solution for both businesses and consumers.
About the Role
The Analytics Engineer is a hands-on technical role within JustPark's data team, sitting at the intersection of data engineering and analytics. You'll be responsible for building and maintaining clean, well-tested data models that power reporting, BI, and business decision-making across our two-sided marketplace. Working closely with the Data Platform and BI teams, you'll help translate raw data into trusted, scalable assets that shape how JustPark makes decisions.
This is an ideal role for someone who is fluent in dbt and BigQuery, enjoys owning modelling problems end-to-end, and can hit the ground running in a fast-moving product environment.
Responsibilities<ul><li>
Build, test, and document dbt models in BigQuery across the staging, intermediate, and mart layers that power analytics and reporting across the business</li><li>
Partner with the BI team and Data Platform Lead to turn business questions into reusable, well-modelled data assets</li><li>
Work with backend engineers to stay ahead of schema changes and resolve data quality issues at source rather than patching them downstream</li><li>
Improve the warehouse over time &mdash; reducing complexity, improving query performance, and keeping BigQuery costs in check</li><li>
Contribute to data governance: documentation, naming standards, discoverability, and exploring how emerging AI tooling can strengthen the data platform</li></ul>
What does success look like in your first 3 months?<ul><li>
You'll have a solid understanding of the existing dbt project, data models, and key reporting areas, and is working independently on modelling tasks with minimal direction</li><li>
You shipped well-structured, tested dbt models that analysts and stakeholders can trust and use, and identified at least one area of the warehouse to meaningfully improve</li><li>
You built effective working relationships with the BI team, Data Platform Lead, and backend engineers, staying ahead of schema changes rather than reacting to them</li><li>
Documentation and governance contributions are in place, making it easier for the team to build on the work going forward</li></ul> 

Requirements 
Must-haves<ul><li>
4+ years of hands-on dbt Core experience in a production environment</li><li>
Proficient in SQL and comfortable with modern data warehouse concepts such as dimensional modelling and layered architecture</li><li>
Practical cloud data warehouse experience, with the ability to write efficient queries and a solid understanding of how to improve performance</li><li>
Translates business requirements into delivery, comfortable working from a business problem through to a shipped model</li><li>
Understands the distinction between transactional and analytical systems, and how backend schema changes can affect downstream data models</li><li>
Comfortable working in a git-based development workflow, including pull requests, code reviews, and contributing to team coding standards</li><li>
Takes ownership of data quality in the models they build, proactively identifying and resolving issues rather than treating it as someone else's problem</li><li>
Curiosity about AI applications in data, including how modern tooling and semantic layers can be leveraged to build more intelligent data products</li></ul>
Nice-to-haves<ul><li>
Experience with dbt Cloud and BigQuery, including scheduling, orchestration, and warehouse optimisation</li><li>
Familiarity with Tableau or supporting analysts who use BI tools</li><li>
Experience building semantic layers, ideally with an understanding of how they support LLM and AI applications</li><li>
Experience with CDC pipelines or event-driven data architectures</li><li>
Python for data transformation or automation tasks</li></ul> 

Benefits 
Recharge your batteries<ul><li>
Generous holiday policy: 25 days + bank holidays + managers can grant up to 5 extra days for high performance (total of 38 days a year)</li><li>
Free lunch on all office days via Feedr with daily meal choice</li><li>
Free snacks &amp; drinks on all office days</li></ul>
Investment in you and your wellbeing<ul><li>
Private Medical Insurance with Vitality</li><li>
Life assurance through YuLife</li><li>
&pound;25 credit for eye tests per year</li><li>
Free O2 concert tickets through our partnership with the O2</li></ul>
Simplifying journeys so you can breathe easier<ul><li>
&pound;50 parking credit per month via JustPark</li><li>
Cycle-to-work salary sacrifice scheme</li><li>
EV salary sacrifice car scheme via Octopus Energy</li></ul>
We look out for your family<ul><li>
Enhanced parental leave with 6-months enhanced maternity leave and 4 weeks fully-paid paternity leave</li><li>
Help finding great childcare with funded hours via Koru Kids</li></ul>
Look after the pennies<ul><li>
Competitive pension offering with standard and salary sacrifice options</li></ul>
Success is best when it's shared<ul><li>
Quarterly away days with the whole UK team</li><li>
Quarterly team social budget</li><li>
Social activities and celebrations on our gorgeous rooftop in King's Cross</li></ul>
Our Interview Process<ul><li>
First-stage - 30-minute virtual video interview via Google Meet with the People Team to tell you more about JustPark and the role and learn more about your experience</li><li>
Second-stage - 45-minute virtual video interview via Google Meet with the Hiring Manager</li><li>
Third-stage - Take home task - We always make sure that the task is relevant for the role and as efficient as possible. Our tasks vary in length based on role &amp; seniority but the task wouldn&rsquo;t take longer than a max. of 3-4 hours to complete</li><li>
Final stage - A 1 hour final interview in our lovely office in Kings Cross, where the team will ask you some questions on your task approach, any learnings and wider final interview-type questions</li></ul></div>

Analytics Engineer

<div>
 
 
 About JustPark
 
 
 
 JustPark is the premier partner offering both B2B solutions for destinations and B2C services for drivers, giving us the best of both worlds. We simplify the entire parking experience. From venues and councils to private driveways, our platform makes it simple for drivers to find, book, and pay for parking, while empowering our operating partners to deliver exceptional parking experiences.
 
 
 We've always believed parking should be easier, from end to end. That's why we, two trailblazing companies - ParkHub and JustPark - have come together to make that vision a reality.
 
 
 ParkHub revolutionized event parking in the US, optimizing venue operations for a smoother, stress-free experience. JustPark transformed parking in the UK, turning the hunt for a spot into a simple, seamless task.
 
 
 Now, as one unified company, we're combining expertise to offer a full-service, frictionless parking solution for both businesses and consumers.
 
 
 
 
 
 
 About the Role
 
 
 
 The Analytics Engineer is a hands-on technical role within JustPark's data team, sitting at the intersection of data engineering and analytics. You'll be responsible for building and maintaining clean, well-tested data models that power reporting, BI, and business decision-making across our two-sided marketplace. Working closely with the Data Platform and BI teams, you'll help translate raw data into trusted, scalable assets that shape how JustPark makes decisions.
 
 
 This is an ideal role for someone who is fluent in dbt and BigQuery, enjoys owning modelling problems end-to-end, and can hit the ground running in a fast-moving product environment.
 
 
 
 
 
 
 Responsibilities
 
 
 <ul>
 <li>
 Build, test, and document dbt models in BigQuery across the staging, intermediate, and mart layers that power analytics and reporting across the business
 </li>
 <li>
 Partner with the BI team and Data Platform Lead to turn business questions into reusable, well-modelled data assets
 </li>
 <li>
 Work with backend engineers to stay ahead of schema changes and resolve data quality issues at source rather than patching them downstream
 </li>
 <li>
 Improve the warehouse over time &mdash; reducing complexity, improving query performance, and keeping BigQuery costs in check
 </li>
 <li>
 Contribute to data governance: documentation, naming standards, discoverability, and exploring how emerging AI tooling can strengthen the data platform
 </li>
 </ul>
 
 
 
 
 
 What does success look like in your first 3 months?
 
 
 <ul>
 <li>
 You'll have a solid understanding of the existing dbt project, data models, and key reporting areas, and is working independently on modelling tasks with minimal direction
 </li>
 <li>
 You shipped well-structured, tested dbt models that analysts and stakeholders can trust and use, and identified at least one area of the warehouse to meaningfully improve
 </li>
 <li>
 You built effective working relationships with the BI team, Data Platform Lead, and backend engineers, staying ahead of schema changes rather than reacting to them
 </li>
 <li>
 Documentation and governance contributions are in place, making it easier for the team to build on the work going forward
 </li>
 </ul>
 
 
 
 
 
 Requirements
 
 
 
 
 Must-haves
 
 
 <ul>
 <li>
 4+ years of hands-on dbt Core experience in a production environment
 </li>
 <li>
 Proficient in SQL and comfortable with modern data warehouse concepts such as dimensional modelling and layered architecture
 </li>
 <li>
 Practical cloud data warehouse experience, with the ability to write efficient queries and a solid understanding of how to improve performance
 </li>
 <li>
 Translates business requirements into delivery, comfortable working from a business problem through to a shipped model
 </li>
 <li>
 Understands the distinction between transactional and analytical systems, and how backend schema changes can affect downstream data models
 </li>
 <li>
 Comfortable working in a git-based development workflow, including pull requests, code reviews, and contributing to team coding standards
 </li>
 <li>
 Takes ownership of data quality in the models they build, proactively identifying and resolving issues rather than treating it as someone else's problem
 </li>
 <li>
 Curiosity about AI applications in data, including how modern tooling and semantic layers can be leveraged to build more intelligent data products
 </li>
 </ul>
 
 
 
 
 
 Nice-to-haves
 
 
 <ul>
 <li>
 Experience with dbt Cloud and BigQuery, including scheduling, orchestration, and warehouse optimisation
 </li>
 <li>
 Familiarity with Tableau or supporting analysts who use BI tools
 </li>
 <li>
 Experience building semantic layers, ideally with an understanding of how they support LLM and AI applications
 </li>
 <li>
 Experience with CDC pipelines or event-driven data architectures
 </li>
 <li>
 Python for data transformation or automation tasks
 </li>
 </ul>
 
 
 
 
 
 Benefits
 
 
 
 
 Recharge your batteries
 
 
 <ul>
 <li>
 Generous holiday policy: 25 days + bank holidays + managers can grant up to 5 extra days for high performance (total of 38 days a year)
 </li>
 <li>
 Free lunch on all office days via Feedr with daily meal choice
 </li>
 <li>
 Free snacks &amp; drinks on all office days
 </li>
 </ul>
 
 
 
 
 
 Investment in you and your wellbeing
 
 
 <ul>
 <li>
 Private Medical Insurance with Vitality
 </li>
 <li>
 Life assurance through YuLife
 </li>
 <li>
 &pound;25 credit for eye tests per year
 </li>
 <li>
 Free O2 concert tickets through our partnership with the O2
 </li>
 </ul>
 
 
 
 
 
 Simplifying journeys so you can breathe easier
 
 
 <ul>
 <li>
 &pound;50 parking credit per month via JustPark
 </li>
 <li>
 Cycle-to-work salary sacrifice scheme
 </li>
 <li>
 EV salary sacrifice car scheme via Octopus Energy
 </li>
 </ul>
 
 
 
 
 
 We look out for your family
 
 
 <ul>
 <li>
 Enhanced parental leave with 6-months enhanced maternity leave and 4 weeks fully-paid paternity leave
 </li>
 <li>
 Help finding great childcare with funded hours via Koru Kids
 </li>
 </ul>
 
 
 
 
 
 Look after the pennies
 
 
 <ul>
 <li>
 Competitive pension offering with standard and salary sacrifice options
 </li>
 </ul>
 
 
 
 
 
 Success is best when it's shared
 
 
 <ul>
 <li>
 Quarterly away days with the whole UK team
 </li>
 <li>
 Quarterly team social budget
 </li>
 <li>
 Social activities and celebrations on our gorgeous rooftop in King's Cross
 </li>
 </ul>
 
 
 
 
 
 Our Interview Process
 
 
 <ul>
 <li>
 First-stage - 30-minute virtual video interview via Google Meet with the People Team to tell you more about JustPark and the role and learn more about your experience
 </li>
 <li>
 Second-stage - 45-minute virtual video interview via Google Meet with the Hiring Manager
 </li>
 <li>
 Third-stage - Take home task - We always make sure that the task is relevant for the role and as efficient as possible. Our tasks vary in length based on role &amp; seniority but the task wouldn&rsquo;t take longer than a max. of 3-4 hours to complete
 </li>
 <li>
 Final stage - A 1 hour final interview in our lovely office in Kings Cross, where the team will ask you some questions on your task approach, any learnings and wider final interview-type questions
 </li>
 </ul>
</div>

LexisNexis Risk Solutions

<div>Are you passionate about building trusted customer data foundations that power meaningful marketing decisions?
Would you like to shape scalable data pipelines and models that improve customer journeys, analytics, and business outcomes?
About the Business
LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business Services vertical, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience. Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication &amp; Verification, Fraud and Credit Risk mitigation and Customer Data Management. You can learn more about LexisNexis Risk at the link below, LexisNexis Risk Solutions | Transform Your Risk Decision Making
About our Team
This role acts as the technical backbone for the Marketing Hub &mdash; partnering closely with analytics, MarTech, and digital teams to deliver the pipelines, data models, and governance frameworks that support personalisation, measurement, experimentation, and strategic decision‑making. The Data Engineer ensures data is not only accurate and compliant but designed for high performance and long‑term growth.
About the Role
The Data Engineer plays a foundational role in enabling modern, insight‑driven marketing by building and maintaining the data infrastructure that powers the organisation&rsquo;s customer intelligence ecosystem. Working across the Customer Data Platform , journey orchestration capability , and advanced analytics and dashboarding environment , the role ensures that marketing has access to trusted, well‑structured, and scalable data.
Responsibilities
<ul><li>Data Architecture &amp; Pipeline Engineering: Build and maintain reliable pipelines integrating customer, campaign, and operational data into the CDP, ensuring accuracy and readiness for analysis
</li><li>Marketing Data Model Design: Develop scalable models supporting segmentation, lifecycle analytics, attribution, and KPI frameworks
</li><li>CDP Enablement &amp; Identity Management: Partner with MarTech and Analytics to improve identity resolution, consent logic, and data quality within the CDP
</li><li>Journey Orchestration Data Readiness: Enable event streams, triggers, and monitoring to support accurate, timely customer journeys
</li><li>Analytics &amp; Dashboarding Enablement: Provide structured datasets and semantic layers for reporting and dashboards, aligned with KPI frameworks
</li><li>Data Governance &amp; Quality Assurance: Maintain data quality, lineage, and compliance with GDPR and PII standards
</li><li>Collaboration &amp; Strategic Influence: Work closely with the Senior Marketing Analyst to align on priorities, translating technical concepts into business insights
</li><li>Operational Excellence &amp; Standards: Ensure scalable, stable data operations using best practices in automation, observability, and continuous improvement
</li></ul>Requirements
<ul><li>Advanced SQL, ETL/ELT frameworks, and cloud data platforms such as Azure, AWS, or GCP
</li><li>Data modelling and pipeline orchestration using tools such as Airflow, Data Factory, dbt, or similar
</li><li>Integrate CDP data sources across digital, CRM, transactional, and behavioural data; support identity resolution, consent handling, audience activation, journey events, trigger logic, and behavioural signals
</li><li>Build data marts and semantic layers for dashboarding and BI tools such as Power BI or Tableau; structure datasets optimised for KPI frameworks, attribution, funnel, and lifecycle analytics
</li><li>Apply data quality frameworks, lineage, cataloguing, and GDPR/PII compliance practices
</li><li>Design secure data pipelines with monitoring, alerting, and SLA/SLO management
</li><li>Translate business and marketing needs into clear technical specifications, communicating technical topics clearly to non-technical stakeholders
</li><li>Partner with analytics, marketing ops, and MarTech teams to own scalable, reliable, trusted customer-data solutions
</li></ul>Risk benefit statement
Learn more about the LexisNexis Risk team and how we work
 
https://relx.wd3.myworkdayjobs.com/RiskSolutions/page/21c296c982531000b79663f3194b0000 

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.
Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here .
Please read our Candidate Privacy Policy .
We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
USA Job Seekers:
EEO Know Your Rights .</div>

Data Engineer

Merlin Entertainments

<div><h2 class="jobSectionHeader">What you'll bring to the team
</h2><div><div><div><div>Senior Data Scientist</div><div>
Location: London/Hybrid</div><div>
Hours: 37.5 hours per week</div><div>
Contract: Permanent - Salaried</div><div></div><div> 
You are a senior technical authority within the Data Science capability. You are responsible not only for building models, but for defining what should be built, ensuring quality, and bridging the gap between business outcomes and technical delivery.</div><div></div><div> 
Responsibilities:</div><ul><li>
Build and deploy predictive models and advanced analytics solutions for high-value use cases.</li><li>
Own the most complex and high-impact modelling problems.</li><li>
Ensure robustness, explainability, and performance of models in production.</li><li>
Define the features and datasets required for modelling.</li><li>
Collaborate with the Lead Data Modeller to shape semantic definitions and structures.</li><li>
Work with Engineering to ensure pipelines support modelling needs.</li><li>
Translate business problems into analytical approaches.</li><li>
Challenge poorly defined requests and drive clarity on outcomes.</li><li>
Communicate trade-offs between model complexity, data availability, and delivery timelines.</li><li>
Establish and enforce best practices for modelling, evaluation, and deployment.</li><li>
Implement peer review processes for models and code.</li><li>
Ensure ethical and responsible use of data and AI.</li><li>
Mentor junior and mid-level Data Scientists.</li><li>
Support capability development and knowledge sharing.</li><li>
Act as a confident voice in shaping Data Science practices.</li><li>
Work closely with the Lead Data Modeller to define &lsquo;Gold&rsquo; data required for analytics.</li><li>
Partner with Data Engineers to ensure model readiness and operational deployment.</li><li>
Align with Delivery Lead on prioritisation and feasibility.</li></ul><div><div><div><div><div><div><div><div> 
Merlin - It's where we playMerlin Entertainments</div><div><div><div>
Merlin Entertainments2.17K subscribers</div></div></div></div></div></div><div></div><div><div><div><div><div>
Watch on</div></div></div></div></div></div></div></div></div><div></div>
</div></div></div><h2 class="jobSectionHeader">Qualifications &amp; Experience
</h2><div><div><div><ul><li>Degree in a relevant field such as Computer Science, Mathematics or Engineering.</li><li>
At least 4 years of experience in a data science or statistical role with a proven track record of delivering impactful solutions.</li><li>
Experience in developing and deploying machine learning models and statistical analysis.</li><li>
Familiarity with distributed computing tools and cloud platforms (e.g., Azure Synapse, Snowflake, Databricks).</li><li>
Experience with data transformation and analytics tools (e.g., Python, SQL, Spark SQL).</li><li>
Proven ability to work with large datasets and complex data structures.</li><li>
Strong background in applying statistical and machine learning techniques to solve business problems.</li></ul>
</div></div></div><h2 class="jobSectionHeader">Benefits
</h2><div><div><div><ul><li>&lsquo;Enjoy the Ride&rsquo; Merlin Annual Passes - 6 in total per year, 1 for you, plus 5 to gift to loved ones!</li>
<li>Merlin Magic Pass - 20 free tickets for you, your family and friends to enjoy all our Merlin Attractions across the world rising to 40 after a year&rsquo;s service</li>
<li>33 days holiday (including bank holidays)</li>
<li>Company bonus</li>
<li>Private pension scheme</li>
<li>40% discount online off LEGO</li>
<li>25% discount in our on-site retail shops and restaurants</li>
<li>Ongoing training and development opportunities</li>
<li>Plus, many more&hellip;</li></ul> 
<div></div>
<div>
If you have any questions or if you require any assistance, because of a disability or medical condition, please contact us by email at Recruitment@Merlinentertainments.biz and one of the team will get back to you as soon as possible.</div>
<div></div>
</div></div></div><h2 class="jobSectionHeader">Pay Range
</h2><div><div><div>Competitive</div></div></div></div>
 <div>At Merlin we welcome the world to our magical attractions and resorts every day and we want to reflect that same multicultural mix inside our business too. We strive to create an inclusive and diverse workplace where people can be themselves, have the same opportunities and thrive together. Because at Merlin, everyone matters!
 
 
Together, we work to create a workplace where everyone feels valued, no matter their age, race, gender, disability or sexual orientation. Although we understand that we'll always be learning and growing, we aim to be the most inclusive and flexible employer in our industry.</div>

SENIOR DATA SCIENTIST

Lendable

<div><h2 class="jobSectionHeader">About Lendable</h2>
Lendable is on a mission to build the world's best technology to help people get credit and save money. We're building one of the world&rsquo;s leading fintech companies and are off to a strong start:<ul><li>
One of the UK&rsquo;s newest unicorns with a team of just over 700 people</li><li>
Among the fastest-growing tech companies in the UK</li><li>
Profitable since 2017</li><li>
Backed by top investors including Balderton Capital and Goldman Sachs</li><li>
Loved by customers with the best reviews in the market (4.9 across 10,000s of reviews on Trustpilot)</li></ul>
So far, we&rsquo;ve rebuilt the Big Three consumer finance products from scratch: loans, credit cards and car finance. We get money into our customers&rsquo; hands in minutes instead of days.
We&rsquo;re growing fast, and there&rsquo;s a lot more to do: we&rsquo;re going after the two biggest Western markets (UK and US) where trillions worth of financial products are held by big banks with dated systems and painful processes.<h2 class="jobSectionHeader">
Join us if you want to</h2><ul><li>
Take ownership across a broad remit. You are trusted to make decisions that drive a material impact on the direction and success of Lendable from day 1</li><li>
Work in small teams of exceptional people, who are relentlessly resourceful to solve problems and find smarter solutions than the status quo</li><li>
Build the best technology in-house, using new data sources, machine learning and AI to make machines do the heavy lifting</li></ul>
We're looking for a Senior Analytics Engineer to own the analytical foundation for our US Loans team, the fastest-growing area of the business. In this role, you&rsquo;ll work closely with analysts, product teams, backend engineers, and business stakeholders to improve how data is structured, transformed, and consumed across the company.
The role is fundamentally about building a strong analytical foundation: making it easier for teams to move from question to insight quickly, while maintaining high standards around data quality, scalability, and maintainability.
You&rsquo;ll operate with a high degree of ownership, helping shape the modelling layer, improving how analysts work with data, and ensuring our warehouse remains a strategic asset for the business.<h2 class="jobSectionHeader">
What you'll be doing</h2><ul><li>
Owning and improving the data models that support lending decisions, pricing, portfolio analysis, and investor reporting.</li><li>
Driving the development of our dbt models and transformation layer, working with analysts and stakeholders to improve the speed and quality of insight generation.</li><li>
Helping define good modelling patterns, architecture, and implementation standards across the analytics engineering layer.</li><li>
Supporting and mentoring analysts at different technical levels, helping them build stronger engineering habits and become more effective with data.</li><li>
Acting as a bridge between analysts, backend engineers, product teams, and the data platform team to make sure data is generated, modelled, and used effectively.</li><li>
Identifying opportunities to improve the efficiency, reliability, and cost-effectiveness of our transformation pipeline over time.</li><li>
Scaling our data infrastructure to proactively support the requirements of a rapidly growing business.</li></ul><h2 class="jobSectionHeader">
Our modern data stack</h2>
You&rsquo;ll work with a modern analytics stack centred around SQL, Snowflake, dbt, Fivetran and Claude.<h2 class="jobSectionHeader">
What we're looking for</h2>
We&rsquo;re looking for someone with strong analytics engineering fundamentals and the ability to apply them pragmatically in a fast-moving environment.
More specifically, we&rsquo;re looking for:
Essential:<ul><li>
Strong SQL skills</li><li>
Strong experience with ELT pipelines and transformation at scale, using dbt.</li><li>
Excellent stakeholder management skills, with a proven ability to influence and negotiate with both technical and non-technical stakeholders</li><li>
Strong data modelling skills and a good understanding of how analytical datasets should be structured for reliability and usability.</li><li>
Good judgement in balancing longer-term platform improvements with day-to-day business needs.</li><li>
The ability to spot inefficiencies in existing data workflows and improve them independently.</li><li>
Comfort using AI tools effectively to move faster, improve quality, and strengthen day-to-day analytical and engineering workflows.</li></ul>
Desirable:<ul><li>
Experience with Snowflake or another modern cloud data warehouse.</li><li>
An interest in helping analysts raise their technical bar through support, mentoring, and better shared patterns.</li><li>
Fintech or scale-up experience</li></ul><h2 class="jobSectionHeader">
Interview process</h2><ul><li>
Initial call with an engineer</li><li>
15 minute Cognitive Assessment</li><li>
Onsite or Video Interview lasting 90 minutes, comprising of:<ul><li>
Introduction of the team and kind of work you could be doing daily</li><li>
Interactive architecture/design exercise</li><li>
Questions you may have about the company, role, etc.</li></ul></li><li>
A 60 minute chat with this role's primary stakeholders<ul><li>
Cultural/behavioural questions</li><li>
Product mindset and ability to collaborate and communicate</li></ul></li></ul><h2 class="jobSectionHeader">
Life at Lendable</h2><ul><li>
Winning team: the opportunity to scale up one of the world&rsquo;s most successful fintech companies</li><li>
Flexible working: flexible approach tailored to each role. Hybrid roles require three days in-office weekly; fully remote roles include regular opportunities for in-person connection through socials and off-sites</li><li>
Socials &amp; connection: opportunities and events to come together, socialise, and get to know each other beyond the office walls</li><li>
Health coverage: support for your physical and mental wellbeing, including private health cover</li><li>
Retirement &amp; savings: long-term financial wellbeing through retirement savings plans</li><li>
Employee referral programme: earn a competitive bonus when you refer successful new team members</li><li>
Office meals &amp; snacks: enjoy a fully stocked kitchen, plus complimentary lunches prepared by in-house chefs on in-office days at select locations</li><li>
Sustainable commuting: cycle-to-work and electric vehicle salary sacrifice schemes available in select locations</li></ul>
Please note: The availability and details of specific benefits vary by location and role. For more information, please speak to your Talent Partner.
Check out our blog!</div>

Senior Analytics Engineer

Capitex

<div>PROGRAMME CONTEXT
Capitex is sourcing specialist resource into the Data workstream of a live Fenergo (Fenx) CLM implementation. The programme is delivering client lifecycle management, KYC/CDD and onboarding capability for a regulated financial institution, with the Data workstream responsible for migrating and validating client, entity and due-diligence data into the Fenergo platform.
This role provides hands-on data depth alongside the configuration and testing workstreams, ensuring migrated data is complete, accurate and fit to drive the configured rules, risk scoring and lifecycle journeys.
ROLE OVERVIEW
The Data Analyst owns source-to-target data mapping, migration and validation activity &mdash; translating legacy and golden-source client/entity data into the Fenergo data model and proving its integrity end-to-end. The role works closely with configuration/BA, testing and client-side data owners to deliver clean, reconciled, audit-ready data.
KEY RESPONSIBILITIES
<ul><li>Define and document source-to-target data mapping from legacy systems and golden sources into the Fenergo CLM / entity data model.</li><li>Author data mapping specifications and transformation rules; maintain mapping documentation as requirements evolve.</li><li>Support and execute data migration (ETL) of client, entity, KYC/CDD and supporting document data into Fenergo.</li><li>Design and run data validation and reconciliation &mdash; pre- and post-migration &mdash; including exception handling and remediation.</li><li>Profile source data quality; identify gaps, duplicates and anomalies and drive resolution with data owners.</li><li>Ensure migrated data correctly supports configured risk rules, scoring and workflow triggers, liaising with the configuration workstream.</li><li>Produce data quality metrics, reconciliation evidence and audit-ready sign-off artefacts for stakeholders.</li></ul>
ESSENTIAL EXPERIENCE
<ul><li>Hands-on data migration / mapping experience on a Fenergo (CLM) implementation.</li><li>Strong source-to-target data mapping and ETL experience on enterprise platform migrations.</li><li>Advanced SQL; confident profiling, validating and reconciling large datasets.</li><li>KYC / CDD / AML data domain knowledge &mdash; client and entity data structures, risk and due-diligence attributes.</li><li>Demonstrable data validation, reconciliation and data-quality discipline on regulated programmes.</li></ul>
DESIRABLE
<ul><li>Banking / Corporate &amp; Institutional Banking or Private/Wealth experience.</li><li>Experience with golden-source / master-data and entity-resolution concepts.</li><li>Oracle / SQL Server, and ETL tooling (e.g. SSIS, DataStage or equivalent).</li><li>SC clearance (or eligibility).</li><li>Exposure to Fenergo rules / event-based messaging and the wider CLM ecosystem.</li></ul>
TOOLS &amp; TECHNICAL ENVIRONMENT
Fenergo CLM, SQL (Oracle / SQL Server), ETL tooling, data profiling and reconciliation tools, JIRA / Confluence; Agile (Scrum / Kanban) delivery environment.</div>

Fenergo CLM Data Analyst / Migration Specialist

Explore 415+ Data modeler in London this July. Find roles across top companies and apply now to boost your career.

415 data modeler jobs In London

[29868] - Data Analytics Engineer - DBT Modelling (Contract)

Analytics Engineer

Analytics Engineer

Data Engineer

SENIOR DATA SCIENTIST

Senior Analytics Engineer

Fenergo CLM Data Analyst / Migration Specialist