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senior data engineer (contract)

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data scientist (data wrangler) Jobs in Leeds

data scientist (data wrangler)

lead data engineer

data scientist

hackajob

<div>
 
 
 hackajob
 
 is collaborating with
 
 Flutter UK&amp;I
 
 to connect them with exceptional professionals for this role.
 
 
 
 
 Your team
 
 
 
 The UKI Data Science team is a cross business chapter sitting in the Customer Super Tribe, working with other areas such as; Safety, Marketing, Gaming, Sports, and more. We work with a range of partners to deliver groundbreaking analytics and AI modelling solutions to help solve business problems.
 
 
 
 What You'll Do
 
 
 
 <ul>
 <li>
 Work with the team to carry out analytical projects involving data collection, pre-processing, feature engineering, model development, validation, and deployment.
 </li>
 <li>
 Engage with business stakeholders to understand domain-specific challenges and opportunities, and collaborate during development to ensure alignment with requirements.
 </li>
 <li>
 Apply advanced statistical and machine learning algorithms to analyse large datasets, uncover patterns, and derive actionable insights to support business objectives.
 </li>
 <li>
 Develop and implement predictive and prescriptive models using machine learning algorithms and techniques, such as regression, classification, clustering, time series analysis, natural language processing, and deep learning.
 </li>
 <li>
 Create clear and compelling visualisations to communicate complex analytical findings effectively.
 </li>
 <li>
 Collaborate with collaborators (including business, product, and engineering) to understand requirements, find opportunities, and provide data-driven recommendations.
 </li>
 <li>
 Collaborate with cross-functional teams to integrate data science solutions into products and services.
 </li>
 <li>
 Engage actively in knowledge sharing, technical, and non-technical discussions within the team.
 </li>
 <li>
 Continuously improve the accuracy, efficiency, and scalability of existing models and algorithms, and identify areas for optimisation and innovation.
 </li>
 <li>
 Maintain high standards of documentation, code quality, and application of best practices in data science and software development.
 </li>
 <li>
 Actively participate in code reviews, pair programming, and knowledge sharing sessions, embracing feedback for continuous improvement.
 </li>
 <li>
 Contribute to building a strong data science team through knowledge sharing and upskilling.
 </li>
 <li>
 Keep abreast of the latest advancements in data science, machine learning, and related fields, and proactively find opportunities to demonstrate the use of new technologies.
 
 
 </li>
 </ul>
 
 How You'll Do It
 
 
 
 <ul>
 <li>
 Proficiency in Python and SQL.
 </li>
 <li>
 Good knowledge of machine learning techniques and algorithms.
 </li>
 <li>
 A demonstrated track record of successfully delivering data science projects.
 </li>
 <li>
 Strong verbal and written communication, ability to explain technical concepts to non technical audiences.
 
 
 </li>
 </ul>
 
 What&rsquo;s On Offer
 
 
 
 <ul>
 <li>
 &pound;/&euro;1,000 learning fund
 </li>
 <li>
 Twice-yearly bonus (with part of it guaranteed!)
 </li>
 <li>
 Unlimited Holiday
 </li>
 <li>
 Pension contribution scheme
 </li>
 <li>
 Private healthcare
 </li>
 <li>
 Hybrid Working -
 </li>
 <li>
 Access to thousands of Udemy courses
 </li>
 <li>
 Invest via the Company Sharesave Scheme
 
 
 </li>
 </ul>
 
 About Flutter UK &amp; Ireland
 
 
 
 Our division operates four of the most popular and trusted brands in the market: Sky Betting and Gaming, Tombola, Betfair and Paddy Power.
 
 
 Together the Flutter UK&amp;I brands offer market leading entertainment to millions of customers every single week! Over the last couple of decades, they have all ridden the wave of digital betting with industry firsts like &lsquo;cash-out&rsquo;, &lsquo;Request a Bet&rsquo;, betting exchanges and free to play games like Soccer Saturday Super 6.
 
 
 
 Working here
 
 
 
 Do you want to work somewhere extraordinary? From the people you spend your days with, to the ground-breaking projects, no two days will be the same.
 
 
 With a philosophy of &lsquo;Together We Are More&rsquo; our 7,000+ colleagues come together to form an expert community across technology, product, commercial, data, infrastructure, marketing, and a myriad of subject areas.
 
 
 We listen without judgement, encourage &amp; support, and help build others up. Working at Flutter UK&amp;I means you can be yourself, work how and where suits you best -and let your personality shine!
</div>

Data Scientist

Are you passionate about using data science to improve healthcare? Join NHS England’s data science teams and play a key role in tackling complex challenges, delivering high-quality insights, and building tools that support better decisions across the NHS.
 
We value modern ways of working, including transparency, reproducibility, agile delivery, and open-source tools. As a Band 7 Data scientist (Data Wrangler), you’ll collaborate with multidisciplinary teams, developing advanced data science methods, building data pipelines, and producing impactful analytical products.
 
If you want to make a real difference through innovative analytics and progress your career in a supportive, collaborative environment, we’d love to hear from you.
 
When applying, please demonstrate your ability in these competency areas: Analytics for Impact, Professional Delivery & Innovation, Engineering, and Leadership & Collaboration.
 
Duties of a Band 7 Data scientist (Data Wrangler) include: 
<ul>
<li>Development and maintenance of data science products</li>
<li>Identification and development of data science applications across policy and operational challenges</li>
<li>Research and horizon scanning for data science in health and care, including active relationships with academia and industry.</li>
<li>Provide support to NHS England and wider health and care sector to enable good use of data science.</li>
<li>Champion adoption of modern ways of working to deliver analytical products (such as transparency, reproducibility, adoption of open-source tools, agile project management)</li>
<li>Communicate analytical insight in an engaging and impactful way</li>
<li>Working in multi-disciplinary teams across NHSE to inject data science expertise into delivery of data products.</li>
<li>Invest in professional development of self and wider team in line with the Data Science Competency Framework for Health and Care professionals.</li>
</ul>
NHS England has a wide range of statutory functions, responsibilities and regulatory powers. These are focused on supporting the wider NHS to deliver high quality care, as well as doing those things that are best done once for the whole NHS.
 
Our staff bring expertise across clinical, operational, commissioning, technology, data science, cyber security, software engineering, education, and commercial specialisms — enabling us to design and deliver high-quality NHS services.
 
In March 2025, the Government announced that NHS England and the Department of Health and Social Care will increasingly merge functions, ultimately leading to NHS England being fully integrated into the department.
 
If you currently work within the NHS and if successful at interview, we will initiate an Inter Authority Transfer (IAT) via the Electronic Staff Record (ESR). This retrieves key data from your current or previous NHS employer to support onboarding, including competency status, Continuous Service Dates (CSD), and annual leave entitlement. You may opt out at any stage of the process.
 
Colleagues with a contractual office base are expected to spend, on average, at least 40% of their time working in our offices.
 
Staff recruited from outside the NHS will usually be appointed at the bottom of the pay band.
 
We cannot offer visa sponsorship for any vacancies.
 
You can find further details about the role, including key responsibilities and accountabilities, alongside the organisational structure and person specification in the attached Job Description and other supporting documents.
 
Your application needs to show evidence of your competence in the following areas:
 
Analytics for impact
 
<ul>
<li>Apply a range of analytical techniques, in consultation with experts if appropriate, and with sensitivity to the limitations of the techniques.</li>
<li>Use expertise to propose techniques appropriate to business problem and characteristics of dataset.</li>
<li>Draw on expertise in several analytical techniques, including their theoretical basis and application.</li>
<li>Identify key messages from analytical work, translating these into terms for use with either technical or non-technical audiences.</li>
<li>Report on your own analytical work in sufficient detail, meeting customer needs, effectively presenting results in both written and oral form.</li>
</ul>
Professional delivery & innovation
 
<ul>
<li>Work with customers to understand their needs, create clear plans and setting priorities which meet the needs of both the customer and the business.</li>
<li>Deliver good customer service which balances quality and cost-effectiveness.</li>
<li>Identify areas of potential risk in own and others' work, selecting and using appropriate Quality Assurance methods and suggesting appropriate mitigation of risk.</li>
<li>Actively identify and take opportunities to promote data science to wider community.</li>
<li>Experiment with innovations, manage and learn from failures and shares lessons learned within the team.</li>
<li>Apply knowledge of new and evolving technologies, including open-source software, suggesting appropriate methods and techniques to incorporate in project work.</li>
</ul>
Engineering
 
<ul>
<li>Use data exploration techniques to understand the characteristics of a dataset, evaluate suitability for subsequent analysis and explain this to other analysts.</li>
<li>Apply data engineering standards and tools to create and maintain data pipelines.</li>
<li>Document and communicate the details of data structures to others.</li>
<li>Design, code, verify, test, document, amend and refactor moderately complex programs/scripts.</li>
<li>Collaborate in reviews of work with others as appropriate.</li>
<li>Proactively adopt practices that ensure rigorous and reproducible findings in development of analytical data products.</li>
</ul>
Leadership & collaboration
 
<ul>
<li>Understand how your work and the work of your team supports wider objectives and meets the diverse needs of stakeholders.</li>
<li>Focus on overall goals and not just specific tasks to meet priorities.</li>
<li>Show pride and passion for your work and positive, inclusive engagement with your team.</li>
<li>Contribute to an inclusive working environment where all opinions and challenges are listened to, and all individual needs are taken into account.</li>
<li>Change ways of working to aid cooperation within and between teams in order to achieve results.</li>
<li>Offer support and help to colleagues when in need, including consideration of your own and their wellbeing.</li>
</ul>
Applicants should use their supporting statement to demonstrate their proven ability across these four areas. Your application will be assessed against these four areas.

Data scientist (Data Wrangler)

Codurance

<div>
 Codurance is a global software consultancy, focused on raising the bar in the software industry through supporting tech communities and working with our clients. We help our clients build remarkable digital products, evolve strategic legacy systems, and equip them to continuously deliver value through the adoption of quality practices and expertise.
 
 
 We are looking for a Contract Senior Data Engineer who shares our values of craftsmanship, pragmatism, and professionalism. You understand that data engineering is, at its core, great software engineering, applied at scale, with rigour, and with production in mind.
 
 
 Databricks is our primary data engineering platform, and you will be expected to use it fluently, but the goal is always durable, well-crafted data systems, not tool advocacy.
 
 
 This is an initial
 
 6-month contract, inside IR35.
 
 
 
 
 What You'll Work On
 
 
 
 Our data engineering engagements fall into three primary shapes:
 
 
 <ul>
 <li>
 Data Foundations
 </li>
 <li>
 Data Modernisation, re-platforming legacy ETL, introducing automated testing and data contracts, and aligning data models with application domains
 </li>
 <li>
 AI-Ready Data Enablement, preparing data systems to safely support AI and ML use cases, including feature pipelines, scalable compute, and guardrails around data quality and lineage
 
 
 </li>
 </ul>
 These engagements sit within wider software modernisation and platform evolution work, not as standalone data projects. You'll work alongside software craftspeople, architects, and client engineers, with data as one part of a broader delivery picture.
 
 
 
 Requirements
 
 
 
 You consider yourself a data engineer with strong software engineering instincts. You care deeply about the quality, testability, and operability of what you build, not just whether it runs.
 
 
 You are comfortable working in small increments, tightening feedback loops, and letting tests inform your pipeline design. You understand that data systems live in production long after they are first delivered, and you build with that in mind.
 
 
 You are a team player who values frequent collaboration with software engineers, data scientists, business analysts and client stakeholders alike. You invest in your craft, stay curious about emerging tooling, and are enthusiastic about sharing what you learn.
 
 
 
 Data Engineering Practices
 
 
 
 You have solid experience applying software engineering disciplines to data: writing testable pipelines, using version control rigorously, and treating data models as first-class software artefacts. You are familiar with data contracts, schema evolution, and the principles of incremental delivery applied to data work.
 
 
 
 Platform and Architecture
 
 
 
 You have hands-on experience with Databricks and are comfortable across its core capabilities: Delta Lake, Unity Catalog, Databricks Workflows, and notebook-to-production pipeline patterns. You have a working understanding of lakehouse architecture and medallion design, and can articulate trade-offs clearly to clients and colleagues.
 
 
 Beyond Databricks, experience with the broader data engineering landscape, including tools such as dbt, Apache Spark, and data quality frameworks, is a plus.
 
 
 
 Data Engineering for ML and AI
 
 
 
 You understand how machine learning and AI systems consume data, and you build the pipelines that feed them to production. You are comfortable with engineering reproducible feature pipelines, managing feature tables in Unity Catalog, and using MLflow for experiment tracking and model registry so that training data and model lineage stay traceable. You prepare and version the datasets that models depend on, and you treat that data with the same rigour you apply to any production system.
 
 
 You are familiar with the data engineering behind modern AI use cases: building embedding and retrieval pipelines, populating and maintaining vector stores, and assembling the evaluation and ground-truth datasets that make model behaviour measurable.
 
 
 
 Software Engineering Foundations
 
 
 
 Your data engineering work is grounded in solid software fundamentals. You understand clean code principles, meaningful abstraction, and the difference between code that works and code that can be maintained. You are familiar with CI/CD applied to data pipelines and are comfortable contributing to infrastructure-as-code environments.
 
 
 
 Observability and Production Readiness
 
 
 
 You understand what it means to run data systems in production. This includes pipeline monitoring, alerting, data quality validation, lineage tracking, and the operational disciplines needed to maintain trust in data over time.
 
 
 
 Cloud Platforms
 
 
 
 You have experience working on at least one major cloud provider (AWS or Azure) and are comfortable with the infrastructure patterns that underpin modern data platforms. Familiarity with cloud-native services for storage, compute, and orchestration is expected.
 
 
 
 Collaboration and Client Engagement
 
 
 
 You can work effectively within a client's environment and communicate clearly with both technical and non-technical stakeholders. You understand how to manage expectations, navigate legacy constraints, and make pragmatic decisions under real-world delivery conditions.
 
 
 
 Legal / Eligibility
 
 
 
 You must be eligible to work in the UK.
</div>

Senior Data Engineer (Contract)

<div>Codurance is a global software consultancy, focused on raising the bar in the software industry through supporting tech communities and working with our clients. We help our clients build remarkable digital products, evolve strategic legacy systems, and equip them to continuously deliver value through the adoption of quality practices and expertise.
We are looking for a Contract Senior Data Engineer who shares our values of craftsmanship, pragmatism, and professionalism. You understand that data engineering is, at its core, great software engineering, applied at scale, with rigour, and with production in mind.
Databricks is our primary data engineering platform, and you will be expected to use it fluently, but the goal is always durable, well-crafted data systems, not tool advocacy.
This is an initial 6-month contract, inside IR35.
What You&rsquo;ll Work On
Our data engineering engagements fall into three primary shapes:<ul><li>
Data Foundations</li><li>
Data Modernisation, re-platforming legacy ETL, introducing automated testing and data contracts, and aligning data models with application domains</li><li>
AI-Ready Data Enablement, preparing data systems to safely support AI and ML use cases, including feature pipelines, scalable compute, and guardrails around data quality and lineage</li></ul>
These engagements sit within wider software modernisation and platform evolution work, not as standalone data projects. You&rsquo;ll work alongside software craftspeople, architects, and client engineers, with data as one part of a broader delivery picture. 
Requirements 
You consider yourself a data engineer with strong software engineering instincts. You care deeply about the quality, testability, and operability of what you build, not just whether it runs.
You are comfortable working in small increments, tightening feedback loops, and letting tests inform your pipeline design. You understand that data systems live in production long after they are first delivered, and you build with that in mind.
You are a team player who values frequent collaboration with software engineers, data scientists, business analysts and client stakeholders alike. You invest in your craft, stay curious about emerging tooling, and are enthusiastic about sharing what you learn.
Data Engineering Practices
You have solid experience applying software engineering disciplines to data: writing testable pipelines, using version control rigorously, and treating data models as first-class software artefacts. You are familiar with data contracts, schema evolution, and the principles of incremental delivery applied to data work.
Platform and Architecture
You have hands-on experience with Databricks and are comfortable across its core capabilities: Delta Lake, Unity Catalog, Databricks Workflows, and notebook-to-production pipeline patterns. You have a working understanding of lakehouse architecture and medallion design, and can articulate trade-offs clearly to clients and colleagues.
Beyond Databricks, experience with the broader data engineering landscape, including tools such as dbt, Apache Spark, and data quality frameworks, is a plus.
Data Engineering for ML and AI
You understand how machine learning and AI systems consume data, and you build the pipelines that feed them to production. You are comfortable with engineering reproducible feature pipelines, managing feature tables in Unity Catalog, and using MLflow for experiment tracking and model registry so that training data and model lineage stay traceable. You prepare and version the datasets that models depend on, and you treat that data with the same rigour you apply to any production system.
You are familiar with the data engineering behind modern AI use cases: building embedding and retrieval pipelines, populating and maintaining vector stores, and assembling the evaluation and ground-truth datasets that make model behaviour measurable.
Software Engineering Foundations
Your data engineering work is grounded in solid software fundamentals. You understand clean code principles, meaningful abstraction, and the difference between code that works and code that can be maintained. You are familiar with CI/CD applied to data pipelines and are comfortable contributing to infrastructure-as-code environments.
Observability and Production Readiness
You understand what it means to run data systems in production. This includes pipeline monitoring, alerting, data quality validation, lineage tracking, and the operational disciplines needed to maintain trust in data over time.
Cloud Platforms
You have experience working on at least one major cloud provider (AWS or Azure) and are comfortable with the infrastructure patterns that underpin modern data platforms. Familiarity with cloud-native services for storage, compute, and orchestration is expected.
Collaboration and Client Engagement
You can work effectively within a client&rsquo;s environment and communicate clearly with both technical and non-technical stakeholders. You understand how to manage expectations, navigate legacy constraints, and make pragmatic decisions under real-world delivery conditions.
Legal / Eligibility
You must be eligible to work in the UK. 
Benefits</div>

Jaywing

Hours
 
Full Time - 35 hours
 
Location
 
Leeds (3 days in office)
 
Department
 
Data Management / IT
 
Salary
 
TBC
 
Founded in 2018, the mission of Stubben Edge is to do insurance differently, making financial services simple, affordable and accessible. We are seeking to revolutionise financial services and offer our products and brands to a wider audience.
 
We are expanding rapidly, both organically and inorganically. Future acquisitions are on the immediate horizon and the company is looking to quadruple its revenue again over the next 12-18 months. As well as our London headquarters, we now also have offices in India, South Africa, and Guernsey.
 
Role Purpose
 
We are looking for a motivated and enthusiastic Junior Data Engineer to join our growing data team. The ideal candidate has a strong work ethic, a desire to learn, and a passion for data. No prior data engineering experience is required; we will provide all the training and support you need to become a successful data engineer.
 
The role is ideal for individuals looking to start their career in data engineering.
 Key Accountabilities
 
Accurate and Timely Internal Reporting : Ensuring that internal reporting demands are met effectively and in a timely manner.
 
Efficient Data Processing : Contributing to the efficient extraction, transformation, and loading (ETL) of data from various sources.
 
Data Quality and Governance : Adhering to and contributing to the implementation of data governance and quality best practices.
 
Collaborative Project Support : Providing effective data engineering support to wider data team initiatives and projects.
 
Continuous Learning and Development : Actively engaging in learning new data technologies and methodologies to enhance team capabilities.
 
Skills and Experience required
 
A strong desire to learn and develop a career in data engineering.
 
A degree. Ideally a 2:1 or above in Maths, a Science or Data.
 
Excellent problem-solving skills and a drive to understand the 'why' behind the data.
 
Excellent communication skills, with the ability to articulate technical concepts and ask clarifying questions.
 
A strong work ethic coupled with an open and collaborative mindset.
 
A genuine openness to receiving and providing feedback to help the team improve.
 
Familiarity with any programming language (e.g., Python, SQL) is a bonus, but not required.
 
Applicants must have the legal right to work in the UK.
 
What we offer: 
25 days’ holiday plus bank holidays.
 
35-hour working week.
 
Training, development, and the chance to grow in a fast-moving fintech.
 
If you’re ambitious and ready to build your career in financial services, we’d love to hear from you.

Junior Data Engineer

<div>
 
 
 About us:
 
 
 
 Founded in 2018, the mission of Stubben Edge is to do insurance differently, making financial services simple, affordable and accessible. We are seeking to revolutionise financial services and offer our products and brands to a wider audience to work across the group alongside Jaywing.
 
 
 
 
 
 We are expanding rapidly, both organically and inorganically. Future acquisitions are on the immediate horizon and the company is looking to quadruple its revenue again over the next 12-18 months. As well as our London headquarters, we now also have offices in India, South Africa, and Guernsey.
 
 
 
 
 
 
 
 Role Purpose
 
 
 
 
 We are looking for a motivated and enthusiastic Junior Data Engineer to join our growing data team. The ideal candidate has a strong work ethic, a desire to learn, and a passion for data. No prior data engineering experience is required; we will provide all the training and support you need to become a successful data engineer.
 
 
 
 
 
 The role is ideal for individuals looking to start their career in data engineering.
 
 
 
 
 
 
 
 Key Accountabilities
 
 
 
 <ul>
 <li>
 
 Accurate and Timely Internal Reporting
 
 : Ensuring that internal reporting demands are met effectively and in a timely manner.
 </li>
 <li>
 
 Efficient Data Processing
 
 : Contributing to the efficient extraction, transformation, and loading (ETL) of data from various sources.
 </li>
 <li>
 
 Data Quality and Governance
 
 : Adhering to and contributing to the implementation of data governance and quality best practices.
 </li>
 <li>
 
 Collaborative Project Support
 
 : Providing effective data engineering support to wider data team initiatives and projects.
 </li>
 <li>
 
 Continuous Learning and Development
 
 : Actively engaging in learning new data technologies and methodologies to enhance team capabilities.
 </li>
 </ul>
 
 
 
 
 
 
 Skills and Experience required
 
 
 
 <ul>
 <li>
 A strong desire to learn and develop a career in data engineering.
 </li>
 <li>
 A degree. Ideally a 2:1 or above in Maths, a Science or Data.
 </li>
 <li>
 Excellent problem-solving skills and a drive to understand the 'why' behind the data.
 </li>
 <li>
 Excellent communication skills, with the ability to articulate technical concepts and ask clarifying questions.
 </li>
 <li>
 A strong work ethic coupled with an open and collaborative mindset.
 </li>
 <li>
 A genuine openness to receiving and providing feedback to help the team improve.
 </li>
 <li>
 Familiarity with any programming language (e.g., Python, SQL) is a bonus, but not required.
 </li>
 <li>
 Applicants must have the legal right to work in the UK.
 </li>
 </ul>
 
 
 
 
 
 What we offer:
 
 
 <ul>
 <li>
 25 days&rsquo; holiday plus bank holidays.
 </li>
 <li>
 35-hour working week.
 </li>
 <li>
 Training, development, and the chance to grow in a fast-moving fintech.
 </li>
 </ul>
 
 
 
 
 If you&rsquo;re ambitious and ready to build your career in financial services, we&rsquo;d love to hear from you.
 
</div>

CreateFuture

<div>Who we are

CreateFuture is fast becoming the UK's most recognisable digital consultancy, with years of experience building digital products and services for major organisations whilst putting our people first. We have offices in the centre of Edinburgh, Leeds, Manchester, and London as well as remote employees located throughout the country. 


We are a team of creators - whether that's code, project plans, go to market strategies, culture initiatives, marketing campaigns, large language models or people policies. And together, with our clients, we create the future. This has seen us collaborate and partner across a multitude of industries and sectors, with the likes of PayPal, adidas, Natwest, FanDuel and Money Saving Expert, to name just a few. 


Our reputation as a partner determined to deliver high-quality, robust and thoughtful products has enabled us to scale to over 500 people in the last couple of years, and it is our amazing people - along with the safe, supportive and friendly culture we have built - that makes CreateFuture a great place to work. Don't just take our word for it though, we have been recognised by Best Workplaces UK multiple years in a row - across a number of categories - and our employee exit rate is astonishingly low.

Join us on our journey&hellip; Let's create something awesome, together, today. 
About the role and team:

We're looking for an experienced Lead Data Engineer to join our growing Data Practice, specialising in iGaming. You'll work as part of a multidisciplinary team delivering data solutions for some of the world's largest betting and gaming operators &mdash; organisations processing millions of events per day across sportsbook, casino, and exchange platforms.

This is a role for someone who understands the pressures of the iGaming data landscape: sub-second odds feeds, high-stakes data integrity requirements, complex regulatory reporting, and large-scale platform migrations from legacy on-premises estates to cloud-native architectures on AWS.

As a Lead, you'll shape technical direction, mentor engineers, and act as a trusted partner to client data and engineering teams. 

<h1 class="jobSectionHeader">
What you'll be doing</h1>
<ul><li>Leading large-scale data migrations from on-premises or legacy platforms to cloud-native architectures on AWS &mdash; including Lakehouse designs using Databricks or Snowflake</li>
<li>Designing and building low-latency data pipelines that process real-time betting events, odds updates, and market data at high throughput</li>
<li>Implementing robust data integrity controls &mdash; validation, reconciliation, and auditability &mdash; across betting, trading, and customer data domains</li>
<li>Architecting streaming and micro-batch solutions using AWS Kinesis, Apache Kafka, or MSK for real-time sportsbook and in-play data feeds</li>
<li>Working with AWS platform services including S3, Glue, Lambda, Athena, Redshift, Lake Formation, Step Functions, and MWAA</li>
<li>Supporting regulatory and compliance reporting &mdash; ensuring data pipelines meet the auditability and lineage requirements of the UK Gambling Commission and international regulators</li>
<li>Leading and mentoring a team of data engineers, setting standards for code quality, testing, and documentation</li>
<li>Contributing to technical proposals, pre-sales scoping, and architecture reviews with iGaming clients</li></ul> 

<h1 class="jobSectionHeader">
We'd love to talk to you if...</h1>
<h2 class="jobSectionHeader">You know the iGaming data landscape</h2>
<ul><li>You've worked in or closely with sportsbook, exchange, or casino platforms &mdash; and understand the data models behind markets, selections, bets, and settlements</li>
<li>You've built or maintained low-latency data feeds &mdash; odds ingestion, in-play event streams, price change feeds &mdash; where milliseconds matter</li>
<li>You understand the data integrity challenges specific to betting: reconciliation between trading and settlement systems, detection of data drift, and auditability for regulatory purposes</li>
<li>You've delivered or contributed to large-scale data migrations &mdash; moving high-volume transactional or event data from legacy estates to the cloud without losing fidelity or uptime</li></ul> 

<h2 class="jobSectionHeader">
You're strong on AWS data engineering</h2>
<ul><li>AWS is your primary cloud &mdash; you're confident across Glue, Lambda, Athena, S3, Redshift, RDS, Kinesis, MSK, and Step Functions</li>
<li>You've built real-time or near-real-time pipelines using streaming frameworks &mdash; Kinesis Data Streams, Kafka, Flink, or Spark Streaming</li>
<li>You understand AWS cost models and how to optimise high-throughput workloads &mdash; Spot compute, reserved capacity, and right-sizing for event-driven architectures</li>
<li>AWS certifications are a bonus &mdash; Solutions Architect or Data Analytics Specialty</li></ul> 

<h2 class="jobSectionHeader">
You know your tools</h2>
<ul><li>Solid experience with Python, SQL, and Spark &mdash; and pipeline tools such as dbt or Airflow</li>
<li>Comfortable with data quality frameworks and testing &mdash; Great Expectations, dbt tests, or custom validation layers</li>
<li>Experience with infrastructure-as-code (Terraform, AWS CDK) is a plus</li>
<li>Familiar with broader cloud platforms &mdash; Azure (Data Factory, Synapse) or GCP (Dataflow, BigQuery) &mdash; is beneficial but not essential</li></ul> 

<h2 class="jobSectionHeader">
You thrive in a consultancy setting</h2>
<ul><li>You've led or mentored data engineers and are comfortable owning technical direction on a complex engagement</li>
<li>You can navigate the politics of a large operator &mdash; multiple teams, competing priorities, and legacy systems that can't just be switched off</li>
<li>You balance hands-on delivery with client engagement, and know when to push back on scope and when to be pragmatic</li></ul> 

<h1 class="jobSectionHeader">
Tech snapshot</h1>
<div>
<div><div><div>Primary cloud</div><div> 

AWS &mdash; Glue, Lambda, Athena, S3, Redshift, RDS, Kinesis, MSK, Lake Formation, Step Functions, MWAA</div></div><div> 
<div>
Streaming</div><div> 

AWS Kinesis, Apache Kafka / MSK, Apache Flink, Spark Streaming</div></div><div> 
<div>
Languages</div><div> 

Python, SQL, Spark</div></div><div> 
<div>
Pipeline tools</div><div> 

dbt, Airflow / AWS MWAA, AWS Glue</div></div><div> 
<div>
Platforms</div><div> 

Databricks, Snowflake, Amazon Redshift</div></div><div> 
<div>
Data quality</div><div> 

Great Expectations, dbt tests, custom reconciliation frameworks</div></div><div> 
<div>
IaC / DevOps</div><div> 

Terraform, AWS CDK (desirable)</div></div> 
</div>
</div><div><h3 class="jobSectionHeader">What we'll offer you:</h3>

We trust people to do their best work. That means flexibility over rigid rules, impact over activity, and real investment in your growth both professionally and personally. You'll be part of a supportive, and friendly culture, surrounded by smart, curious people who care deeply about what they do. 
 
We offer flexible working, including hybrid and remote options. Our office hubs are located in Edinburgh, Leeds, Manchester, London and Bulgaria, with occasional travel to client sites or CreateFuture offices when needed.

We trust you to manage your time balancing collaboration with client time and focused work. What matters is the impact you have, not how busy you look.
<h3 class="jobSectionHeader">
Our hiring process</h3>

We try to keep our hiring process clear, fair and respectful of your time. We aim to get back to everyone who applies and we will be upfront about where you are in the process.

It usually looks like this:
<ul>
<li>Call with our Talent Acquisition Team</li>
<li>Role specific capability interview</li>
</ul>
Depending on the role, we might also ask you to do a short presentation, a practical or technical task or have a values focused conversation. We will explain what is involved before anything happens.
<h3 class="jobSectionHeader">
Inclusion at CreateFuture</h3>

We believe diverse teams build better workplaces and better products. We want CreateFuture to be a place where people feel able to be themselves and do their best work.

If you need any adjustments or support during the application process, just. We will do what we can to help.

We look forward to your application!</div></div>

Lead Data Engineer

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