data engineer

ai engineer

senior ai engineer

senior data engineer

analytics engineer

analytics architect

Luxoft

<div><div><h5 class="jobSectionHeader"><b>Project description
</b></h5><p>We are seeking a Data Architect to join our AI project team. In this role, you will design and implement the data architecture needed to support machine learning and AI solutions, including defining data models, storage patterns, and governance frameworks. You will ensure that data from various sources is well-organised, accessible, and AI-ready, working closely with data engineers and ML engineers to build robust data pipelines and maintain high data quality for analytics and model development.
</p></div><div><h5 class="jobSectionHeader"><b>Responsibilities</b></h5>
<div><div><p>Data Modelling &amp; Schema Design: Develop and maintain data models (conceptual, logical, and physical) that define how data is stored and related. This includes designing relational schemas, graph data models for knowledge graphs, and time-series data structures as needed, ensuring they accurately represent business entities and relationships. You will continually refine these models to meet AI use cases and evolving business requirements.
</p></div><div><p>Data Storage Architecture: Define and implement data storage and management patterns that optimise data retrieval and analytics performance. This involves selecting or designing appropriate storage solutions (e.g. relational databases, NoSQL/graph databases, data warehouses, data lakes) and structuring them for scalability and fast access to large datasets used in AI projects. Ensure the architecture can handle structured and unstructured data and is cloud-ready for elasticity.
</p></div><div><p>Data Pipelines &amp; Integration: Build and oversee robust data pipelines (ETL/ELT processes) to integrate data from multiple sources into centralised platforms. You will design workflows to collect, transform, and load data into analytics repositories or feature stores, guaranteeing that AI models have consistent, well-prepared data to work with. This includes setting up stream processing for real-time data when required and automating pipeline orchestration for efficiency.
</p></div><div><p>Data Governance &amp; Quality: Establish and enforce data governance policies and standards. This means defining practices for data quality, data cleaning, and master data management, as well as setting security and privacy controls to protect sensitive information. You will ensure compliance with relevant data regulations and implement data security measures (e.g. access controls, encryption) and validation rules so that the data used in AI is trustworthy and compliant.
</p></div><div><p>Metadata Management &amp; Lineage: Implement frameworks for data metadata management and lineage tracking. This includes maintaining data catalogues or dictionaries that describe data meaning (possibly leveraging ontologies), and tools or processes to trace how data flows through pipelines and transformations. By providing transparency into data origins and transformations, you support model interpretability and enable troubleshooting of data issues, which is critical in AI development.
</p></div><div><p>Collaboration with Engineering Teams: Work closely with data engineers, ML engineers, and data scientists to ensure the data architecture meets their needs. You will collaborate on designing data interfaces (e.g. APIs or query endpoints) and assist in shaping how data is used for features in machine learning. This role requires translating requirements between data teams and ML teams, and jointly resolving issues to streamline the path from raw data to AI insights.
</p></div><div><p>Performance Optimisation &amp; Scaling: Monitor the performance and scalability of the data infrastructure, and tune it as the AI project grows. Optimise database queries, indexing, and storage layouts for faster model training and inference data access. Plan for scale by leveraging cloud capabilities (compute, storage) and manage costs effectively, adjusting architectures (partitioning, caching, etc.) to maintain efficient, cost-effective operations as data volumes increase. You may also evaluate new technologies (e.g. distributed computing frameworks or new databases) and incorporate them to continually improve the architecture.
</p></div></div></div><div><h5 class="jobSectionHeader"><b>Skills</b></h5>
<p>Must have
</p><div><div><p>Education: Bachelor's degree in Computer Science, Information Systems, or a related field (or equivalent professional experience). An advanced degree is a plus but not required.
</p></div><div><p>Experience: Approximately 3-5 years of experience in data architecture, data engineering, or a related data management role. A proven track record in designing data solutions and managing data schemas is expected.
</p></div><div><p>Data Modelling &amp; Databases: Strong proficiency in data modelling and database design. You should be comfortable creating ER diagrams and defining relational schema, as well as working with NoSQL databases (e.g. document or graph databases). Practical experience with SQL and at least one relational database is required, as well as deep knowledge of other data store types (especially graph databases) is highly needed.
</p></div><div><p>Data Pipeline Development: Hands-on experience developing data pipelines and integration workflows. This includes proficiency in ETL/ELT tools or frameworks (or custom scripting with Python/SQL) to gather and transform data. You should understand how to optimise data flow and have experience with batch processing; experience with real-time streaming data (e.g. using Kafka or equivalent) is a plus.
</p></div><div><p>Ontologies &amp; Knowledge Graphs: Exposure to semantic data modelling, ontologies, or knowledge graph construction. Experience in structuring data with ontologies (e.g. using RDF/OWL standards) or implementing a knowledge graph to link datasets can be very beneficial, since it helps in creating a unified data vocabulary and enriches the context for AI models.
</p></div><div><p>Cloud Data Platforms: Experience working with cloud-based data platforms or big data technologies. While our approach is cloud-agnostic, you should be familiar with concepts like data lakes, data warehouses, and distributed computing in a cloud environment (e.g. using AWS, Azure, or GCP services). The ability to design solutions that leverage cloud scalability and tools for storage and processing is important.
</p></div><div><p>Data Governance &amp; Security: Solid understanding of data governance principles and best practices. You should be knowledgeable about data privacy regulations and data protection techniques, ensuring compliance in how data is stored and used. Experience implementing data quality checks, defining data standards, and using or setting up metadata management tools will be useful.
</p></div><div><p>Communication &amp; Teamwork: Excellent communication skills with the ability to collaborate in cross-functional teams. You should be able to translate complex data architecture concepts into clear terms for project managers or stakeholders, and work closely with engineering teams to guide implementation. Problem-solving aptitude and a willingness to mentor junior data team members are also important in our collaborative environment.
</p></div></div><p>Nice to have
</p><div><div><p>AI/ML Project Involvement: Experience working on projects that involve AI or machine learning, where you partnered with data scientists or ML engineers. For example, having supported an ML model deployment by providing well-structured data and ensuring data reliability. This background will help you anticipate the needs of AI initiatives and design data architectures that facilitate model training and inference.
</p></div><div><p>Data Governance Tools: Familiarity with data governance or data cataloguing tools (such as Collibra, Alation, or Apache Atlas) and lineage-tracking systems. Hands-on experience setting up or maintaining a data catalogue, documenting data definitions, or automating data lineage capture is a strong plus, as it shows ability to operationalise governance and transparency in data ecosystems.
</p></div><div><p>Modern Data Architecture Patterns: Experience with modern data architecture concepts and patterns. This could include implementing or working with data lakehouse architectures (combining data lake flexibility with data warehouse performance), data mesh principles (decentralising data ownership to domain teams), or event-driven/streaming architectures. Familiarity with these approaches demonstrates adaptability and knowledge of cutting-edge solutions for handling complex data workflows.
</p></div><div><p>Certifications: Relevant industry certifications are advantageous. Certifications such as AWS/Azure/GCP data engineering certifications, Certified Data Management Professional (CDMP), or other credentials in data architecture and cloud services show validated expertise and a commitment to staying current with technology developments. While not mandatory, they could strengthen your candidacy.
</p></div></div></div><div><h5 class="jobSectionHeader"><b>Other</b></h5>
<div><div><div><p>Languages</p>
<p>English: C1 Advanced
</p></div></div><div><div><p>Seniority</p>
<p>Senior</p></div></div></div></div></div>
<br><div><div><div><p>London, United Kingdom of Great Britain and Northern Ireland
</p></div><p>Req. VR-123709
</p></div><div></div><div><div><p>AI/ML
</p></div><div><p>BCM Industry</p>
</div><div><p>30/06/2026
</p></div><div><p>Req. VR-123709</p></div></div></div><p></p>

Data Architect

The Law Society

<div></div><div><div><div><div><div><p>Join the Law Society's Data and AI team at an exciting stage of our data transformation journey. Having recently implemented our first enterprise Data Platform, we're looking for an Analytics Engineer to help shape the next phase of our data and analytics capability.</p>
<p>
In this role, you will design, build and maintain trusted data models and analytics products that enable reporting, generate valuable insights and support informed decision-making across the organisation.</p>
<p>
Working closely with data engineers, analysts and business stakeholders, you'll transform complex data into well-governed, reusable analytical models that power reporting tools such as Power BI. You'll also play a key role in improving data quality, enhancing data accessibility and ensuring colleagues can confidently find, trust and use data to drive business outcomes.</p>
<p>
This is an excellent opportunity to join a knowledgeable and growing Data and AI team where you'll have the chance to influence best practice, work with modern technologies and contribute to the continued evolution of our data platform.</p>
</div></div></div></div><div><div><div><h2 class="jobSectionHeader"><b>What we're looking for</b></h2></div>
</div></div><div><div><div><div><p>We're looking for someone with a passion for data and analytics who can bridge technical expertise with business needs. You will have:</p>
<ul>
<li>Strong SQL skills and experience designing reliable, scalable and maintainable data models, optimised for BI tools such as Power BI.</li>
<li>Experience developing reports, dashboards and semantic models using Power BI or similar analytics platforms.</li>
<li>Knowledge of modern cloud data technologies such as Databricks, Snowflake or Azure Data Factory.</li>
<li>An understanding of data governance, data lineage and data quality principles.</li>
<li>The ability to work collaboratively with stakeholders to translate business requirements into practical data solutions.</li>
<li>A proactive, collaborative approach with a commitment to continuous improvement.</li>
</ul>
<p><b>Desirable skills include:</b></p>
<ul>
<li>Experience using Git and Python.</li>
<li>Experience working within Agile delivery environments.</li>
<li>Relevant cloud or data certifications.</li>
</ul></div></div></div></div><div><div><div><h2 class="jobSectionHeader"><b>What's in it for you</b></h2></div>
</div></div><div><div><div><div><p>This is an exciting opportunity to join a respected membership organisation with a strong reputation for excellence and legal expertise. You'll work alongside talented colleagues who are passionate about using data to deliver meaningful impact across the organisation.</p>
<p>
At the Law Society, we're committed to fostering an inclusive workplace where equality, diversity and inclusion are valued, and where our culture is built on trust, clarity, excellence and respect.</p>
<p>
We offer:</p>
<ul>
<li>Hybrid working.</li>
<li>A generous and flexible benefits package.</li>
<li>A supportive and collaborative working environment.</li>
<li>Excellent opportunities for learning, development and career progression.</li></ul><br>
<p>
<br>
<i>Please note: i</i><i>f you are an internal applicant, Pay Policy will apply.</i><br>
</p><p><b>The Law Society represents solicitors in England and Wales. From negotiating with and lobbying the profession's regulators, government and other decision makers, to offering training and advice, we're here to help, protect and promote solicitors.</b></p></div></div></div></div></div>

Analytics Engineer

Anthropic

<div><div><h2 class="jobSectionHeader"><b>About Anthropic</b></h2>
<p>
Anthropic&rsquo;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p></div><div><h2 class="jobSectionHeader"><b>
About the role</b></h2>
<p>
As a Partners Solutions Architect on the Applied AI team at Anthropic, you will be a Pre-Sales architect focused on cultivating technical relationships with our Global and Regional System Integrators (GSIs/RSIs), and our cloud partners (AWS and GCP). You will strengthen our relationships with key partners to accelerate indirect revenue, enable their AI practices, and execute on long-term GTM strategy.</p>
<h2 class="jobSectionHeader"><b>
Responsibilities:</b></h2>
<ul>
<li><p><b>Strategic Technical Partnership</b>: Be a technical thought partner to the Anthropic GTM partnerships team, providing technical expertise to better understand the partner landscape, driving key strategic programs, and identifying opportunities to deepen partner technical capabilities. Embed with GSI and cloud partner technical teams to enable their AI practices, support troubleshooting, evangelize Anthropic in their developer communities, and serve as an escalation point for complex technical issues.</p>
</li>
<li><p><b>Joint Solution Development:</b> Collaborate with partners to identify high value industry-specific GenAI applications, develop joint solutions and codify reference architectures / best practices to accelerate time to deployment</p>
</li>
<li><p><b>Customer Deal Support:</b> Intervene directly to unblock strategic customer deals where partners are the primary delivery vehicle, providing deep technical expertise and solution architecture guidance.</p>
</li>
<li><p><b>Partner Ecosystem &amp; Events: </b>Represent Anthropic at partner events such as GSI customer workshops, AWS summits, and industry conferences. Lead or support partner-specific developer events, hackathons, and technical enablement sessions, especially for technically native communities.Product Feedback: Validate and gather feedback on Anthropic's products and offerings, especially as they relate to partner use cases and deployment patterns, and deliver this feedback to relevant Anthropic teams to inform product roadmap and partner strategy.</p>
</li>
</ul><h2 class="jobSectionHeader"><b>You may be a good fit if you have:</b></h2>
<ul>
<li><p>5+ years of experience in technical customer-facing/partner-facing roles such as Solutions Architect, Sales Engineer, Partner Sales Engineer, Technical Account Manager</p>
</li>
<li><p>Track record of successfully partnering with GSIs and/or cloud providers to solve complex technical challenges, from initial solution design through customer delivery</p>
</li>
<li><p>Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering &amp; IT teams, and more</p>
</li>
<li><p>Strong presentation &amp; technical communication skills with the ability to translate requirements between technical and business stakeholders</p>
</li>
<li><p>Experience designing scalable cloud architectures and integrating with enterprise systems</p>
</li>
<li><p>Familiarity with common LLM frameworks and tools or a background in machine learning or data science</p>
</li>
<li><p>Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities</p>
</li>
<li><p>A love of teaching, mentoring, and helping others succeed</p>
</li>
<li><p>Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems</p>
</li>
</ul></div><div><div><div><div><p>The annual compensation range for this role is listed below.</p>
<p>
For sales roles, the range provided is the role&rsquo;s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.</p></div></div><p>
Annual Salary:</p><p>
&pound;165,000 - &pound;190,000 GBP</p></div></div><div><h2 class="jobSectionHeader"><b>
Logistics</b></h2>
<p><b>
Minimum education: </b>Bachelor&rsquo;s degree or an equivalent combination of education, training, and/or experience</p>
<p><b>
Required field of study: </b>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><b>
Minimum years of experience: </b>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><b>
Location-based hybrid policy:</b> Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</p>
<p><b>
Visa sponsorship:</b> We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</p>
<p><b>
We encourage you to apply even if you do not believe you meet every single qualification.</b> Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.<br>
<br>
<b>Your safety matters to us.</b> To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links&mdash;visit anthropic.com/careers directly for confirmed position openings.</p>
<h2 class="jobSectionHeader"><b>
How we're different</b></h2>
<p>
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact &mdash; advancing our long-term goals of steerable, trustworthy AI &mdash; rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.</p>
<p>
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2 class="jobSectionHeader"><b>
Come work with us!</b></h2>
<p>
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. <b>Guidance on Candidates' AI Usage:</b> Learn about our policy for using AI in our application process.</p></div></div>

Applied AI Architect, Partnerships

Lendable

<div><h2 class="jobSectionHeader"><b>About Lendable</b></h2><p>
Lendable is on a mission to build the world's best technology to help people get credit and save money.<b> </b>We're building one of the world&rsquo;s leading fintech companies and are off to a strong start:</p><p></p><ul><li><p>
One of the UK&rsquo;s newest unicorns with a team of just over 700 people</p></li><li><p>
Among the<b> fastest-growing tech</b> companies in the UK</p></li><li><p>
Profitable since <b>2017</b></p></li><li><p>
Backed by top investors including <b>Balderton Capital </b>and<b> Goldman Sachs</b></p></li><li><p><b>
Loved by customers</b> with the best reviews in the market (4.9 across 10,000s of reviews on Trustpilot)</p></li></ul><p></p><p>
So far, we&rsquo;ve rebuilt the Big Three consumer finance products from scratch:<b> loans, credit cards and car finance</b>. We get money into our customers&rsquo; hands in minutes instead of days.</p><p></p><p>
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 <b>with dated systems and painful processes.</b></p><p></p><h2 class="jobSectionHeader"><b>
Join us if you want to</b></h2><ul><li><p><b>
Take ownership </b>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</p></li><li><p><b>
Work in small teams of exceptional people,</b> who are relentlessly resourceful to solve problems and find smarter solutions than the status quo</p></li><li><p><b>
Build the best technology in-house</b>, using new data sources, machine learning and AI to make machines do the heavy lifting</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
About the role</b></h2><p>
We're looking for an analytics engineer to contribute to the analytical foundation of the UK Motor team, a rapidly-growing area of the business.</p><p>
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.</p><p>
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.</p><p>
You'll contribute to the modelling layer, help improve how the business work with data, and support the team in keeping our warehouse a reliable, strategic asset for the business.</p><p></p><h2 class="jobSectionHeader"><b>
What you'll be doing</b></h2><ul><li><p>
Building and improving the data models that support lending decisions, pricing, portfolio analysis, and investor reporting.</p></li><li><p>
Championing standards and contributing to the improvement of our analytics engineering culture.</p></li><li><p>
Supporting and collaborating with analysts at different technical levels,helping translate requirements into robust pipelines</p></li><li><p>
Helping triage and resolve issues that affect the analytics pipeline or reduce trust in downstream datasets, and contributing ideas to improve the efficiency, reliability, and cost-effectiveness of our transformation pipeline over time.</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
Our modern data stack</b></h2><p>
You&rsquo;ll work with a modern analytics stack centred around SQL, Snowflake, dbt, Fivetran and Claude.</p><p></p><h2 class="jobSectionHeader"><b>
What we're looking for</b></h2><p>
We&rsquo;re looking for someone with solid analytics engineering fundamentals and the ability to apply them pragmatically in a fast-moving environment and explain tradeoffs to stakeholders with varying technical depth.</p><p>
More specifically, we&rsquo;re looking for:</p><ul><li><p>
Strong data modelling skills and a good understanding of how analytical datasets should be structured for reliability and usability.</p></li><li><p>
Strong experience with ELT pipelines and transformation at scale, ideally using dbt.</p></li><li><p>
Experience with Snowflake or another modern cloud data warehouse.</p></li><li><p>
Proactiveness in raising areas of data workflows that could be improved and suggesting solutions.</p></li><li><p>
A collaborative working style and clear communication across technical and non-technical stakeholders.</p></li><li><p>
Comfort using AI tools effectively to move faster, improve quality, and strengthen day-to-day analytical and engineering workflows</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
Interview process</b></h2><ul><li><p>
Initial call with an engineer</p></li><li><p>
15 minute Cognitive Assessment</p></li><li><p>
Onsite or Video Interview lasting 90 minutes, comprising of:</p><ul><li><p>
Introduction of the team and kind of work you could be doing daily</p></li><li><p>
Interactive architecture/design exercise</p></li><li><p>
Questions you may have about the company, role, etc.</p></li></ul></li><li><p>
A 60 minute chat with this role's primary stakeholders</p><ul><li><p>
Cultural/behavioural questions</p></li><li><p>
Product mindset and ability to collaborate and communicate</p></li></ul></li></ul><p></p><h2 class="jobSectionHeader"><b>
Life at Lendable</b></h2><ul><li><p><b>
Winning team: </b>the opportunity to scale up one of the world&rsquo;s most successful fintech companies</p></li><li><p><b>
Flexible working: </b>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</p></li><li><p><b>
Socials &amp; connection: </b>opportunities and events to come together, socialise, and get to know each other beyond the office walls</p></li><li><p><b>
Health coverage:</b> support for your physical and mental wellbeing, including private health cover</p></li><li><p><b>
Retirement &amp; savings:</b> long-term financial wellbeing through retirement savings plans</p></li><li><p><b>
Employee referral programme:</b> earn a competitive bonus when you refer successful new team members</p></li><li><p><b>
Office meals &amp; snacks:</b> enjoy a fully stocked kitchen, plus complimentary lunches prepared by in-house chefs on in-office days at select locations</p></li><li><p><b>
Sustainable commuting:</b> cycle-to-work and electric vehicle salary sacrifice schemes available in select locations</p></li></ul><p><b><i>
Please note:</i></b><i> The availability and details of specific benefits vary by location and role. For more information, please speak to your Talent Partner.</i></p><p>
Check out our blog!</p></div>

Bauer Media Group

<b>Location:</b> London, Hybrid [1-2 days per week on site]
<br><br>
<b>Our Team:</b> How we enrich everyday life
<br><br>
You’ll be joining our Data & Decision Sciences (DDS) team at Bauer Media Audio, where we use data to power decisions across nine European markets. We’re a collaborative, cross-functional team working across commercial revenue, digital audiences, and consumer competitions, turning complex data into insights that shape how millions of people engage with our brands every day.
<br><br>
Working closely with Data Engineers, Data Scientists, Product Managers and business stakeholders, we combine central expertise with local market knowledge to deliver real impact.
<br><br>
The difference you will make
<br><br>
As an Analytics Engineer, you’ll play a key role in transforming raw data into trusted, business-ready insights. You’ll help build the data models and semantic layers that underpin reporting and analytics across Bauer Media Audio, enabling teams to make smarter, faster decisions.
<br><br>
This is an exciting opportunity to help modernise our data platform, working with emerging technologies and shaping how data is structured, defined, and consumed across the business.
<br><br>
Your role
<br><br>
You’ll design and build scalable data models and pipelines that translate complex data into meaningful insights for the business.
<br><br>
<b>Responsibilities include, but are not limited to:</b><br>
Design and develop dimensional data models and marts using dbt and Kimball principles
<br>Build and maintain transformation pipelines from raw data to business-ready datasets
<br>Define and evolve semantic layers to ensure consistent metrics and reporting across tools like Looker, Power BI and Tableau
<br>Collaborate with Data Engineers to shape upstream data and improve data pipelines
<br>Implement data quality checks and maintain reliable, trusted datasets
<br>Support the migration and modernisation of legacy data platforms to Snowflake
<br>Maintain documentation including data dictionaries and semantic definitions
<br>Contribute to agile workflows, code reviews, and cross-functional collaboration
<br>Get involved with setting up Airflow DAGs or write Terraform to setup infrastructure.
<br><br>
The skills you will bring
<br><br>
<b>Must-have:</b><br>
Strong SQL skills and experience with modern cloud data warehouses (e.g. Snowflake, Redshift, or BigQuery)
<br>Hands-on experience with dbt for data transformation and modelling
<br>Solid understanding of dimensional modelling (Kimball methodology)
<br>Experience working with BI tools such as Looker or Power BI
<br>Comfort working in agile teams using tools like Jira and GitHub
<br>Strong communication skills with the ability to translate data into business concepts
<br><br>
<b>Nice-to-have:</b><br>
Experience with Snowflake or modern cloud data platforms
<br>Exposure to Airflow, Terraform, or CI/CD practices
<br>Experience with data quality tools such as Great Expectations
<br>Familiarity with Tableau or multi-BI environments
<br>Background in media, digital, or subscription-based businesses
<br>Experience using Python for data and analytics engineering tasks
<br><br>
About Bauer Media Group
<br><br>
We are a media business focused on creating content that matters to millions of people across Europe. Our offering extends from print and online publishing to audio broadcasting and entertainment, alongside investments in other media related sectors. With more than 500 million copies sold each year, we are one of Europe’s largest Publishers. From women’s and celebrities’ magazines to TV listings to food and special interest, we own some of the most popular publishing brands in Germany, UK, Poland and France – both digital and print. But not only that. Reaching over 61 million listeners weekly, we operate over 150 radio and podcast brands in nine countries, spanning the UK, Ireland, Poland, Slovakia, Denmark, Sweden, Finland, Norway and Portugal. Family-owned in the 5th generation, Bauer Media focuses on the long-term, with a consumer-first mindset that guides us across our diverse portfolio. Our workforce of 12,000 shares a common purpose: to deliver content and services that enrich people‘s everyday lives.
<br><br>
What’s in it for you
<br><br>
You’ll have 28 days holiday, bank holidays & 2 volunteer days to use.
<br>Your development matters, so access to our internal training provider – Bauer Academy, is a huge win.
<br>We have enhanced Maternity/Adoption, Paternity and Shared Parental Leave Pay.
<br>You’ll have the opportunity for flexible working.
<br>And much more! Find the full details of our benefits here
<br><br>
We are an international employer and equal opportunities are important to us. That's why we welcome everyone in their uniqueness, regardless of e.g. religion, gender, skin color, disability in our house.
<br><br>
We are committed to ensuring our recruitment process is inclusive and accessible to all. If you have a disability or a long term health condition, and need us to make any reasonable adjustments or do anything differently during any stage of the recruitment process, please let us know by emailing careershub@bauermedia.co.uk
<br><br>
We are actively recruiting for this position, so the job advert may close earlier than expected.
<br><br>
If you have any feedback regarding our UK recruitment process, please email careershub@bauermedia.co.uk we would love to hear from you.
<br><br>
<b>Date Job Posting Last Updated:</b> 25 Jun 2026
<br><br>
<b>Location:</b><br>
London, GB, NW1 2PL
<br><br>
<b>#job-location.job-location-inline { display:</b> inline; }
<br><b>Req ID:</b> 3719

JustPark

<div><p><b>About JustPark</b></p><p>
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.</p><p>
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.</p><p>
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.</p><p>
Now, as one unified company, we're combining expertise to offer a full-service, frictionless parking solution for both businesses and consumers.</p><p><b>
About the Role</b></p><p>
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.</p><p>
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.</p><p><b>
Responsibilities</b></p><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><p></p><p><b>
What does success look like in your first 3 months?</b></p><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><br>
<b>
Requirements</b><p><b><br>
Must-haves</b></p><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><p></p><p><b>
Nice-to-haves</b></p><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><br>
<b>
Benefits</b><p><b><br>
Recharge your batteries</b></p><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><p></p><p><b>
Investment in you and your wellbeing</b></p><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><p></p><p><b>
Simplifying journeys so you can breathe easier</b></p><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><p></p><p><b>
We look out for your family</b></p><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><p></p><p><b>
Look after the pennies</b></p><ul><li>
Competitive pension offering with standard and salary sacrifice options</li></ul><p></p><p><b>
Success is best when it's shared</b></p><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><p></p><p><b>
Our Interview Process</b></p><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>

<div>
 <p>
  <strong>
   About JustPark
  </strong>
 </p>
 <p>
  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.
 </p>
 <p>
  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.
 </p>
 <p>
  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.
 </p>
 <p>
  Now, as one unified company, we're combining expertise to offer a full-service, frictionless parking solution for both businesses and consumers.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   About the Role
  </strong>
 </p>
 <p>
  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.
 </p>
 <p>
  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.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Responsibilities
  </strong>
 </p>
 <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>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What does success look like in your first 3 months?
  </strong>
 </p>
 <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>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Requirements
  </strong>
 </p>
 <p>
  <strong>
   Must-haves
  </strong>
 </p>
 <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>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Nice-to-haves
  </strong>
 </p>
 <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>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Benefits
  </strong>
 </p>
 <p>
  <strong>
   Recharge your batteries
  </strong>
 </p>
 <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>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Investment in you and your wellbeing
  </strong>
 </p>
 <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>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Simplifying journeys so you can breathe easier
  </strong>
 </p>
 <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>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   We look out for your family
  </strong>
 </p>
 <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>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Look after the pennies
  </strong>
 </p>
 <ul>
  <li>
   Competitive pension offering with standard and salary sacrifice options
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Success is best when it's shared
  </strong>
 </p>
 <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>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Our Interview Process
  </strong>
 </p>
 <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>


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