Head of Analytics Engineering

Head of Analytics Engineering

Full-Time 80000 - 100000 £ / year (est.) No working from home possible
Paddle

At a Glance

  • Tasks: Lead a dynamic team to create impactful data solutions and drive analytics strategy.
  • Company: Join Paddle, a forward-thinking tech company revolutionising payment infrastructure.
  • Benefits: Enjoy unlimited holidays, remote work options, and generous family leave.
  • Other info: Be part of a diverse team committed to inclusivity and personal development.
  • Why this job: Shape the future of analytics while fostering a culture of growth and collaboration.
  • Qualifications: Proven leadership in analytics engineering and strong stakeholder management skills required.

The predicted salary is between 80000 - 100000 £ per year.

Paddle offers digital product companies a completely different approach to their payment infrastructure. Instead of assembling and maintaining a complex stack of payments-related apps and services, we’re a Merchant of Record for our customers. That means we take away 100% of the pain of payment fragmentation. It’s faster, safer, cheaper, and, above all, way better. We’re backed by investors including KKR, FTV Capital, Kindred, Notion, and 83North and serve over 5000 software sellers in 245 territories globally.

As an Analytics Engineering Manager, you'll lead a dynamic team, working closely with various business units to translate complex business requirements into actionable data solutions. You will play a critical role in communicating analytics insights clearly and with impact, enabling data-driven decision-making across the organization. Collaboration with Sales, Marketing, Finance, Product Managers, and Engineering teams will be essential to align analytics solutions seamlessly with business objectives and technical capabilities.

What you'll do:

  • Leadership & Strategy
    • Define and own the multi-year technical vision and strategy for Analytics Engineering, ensuring alignment with Paddle's product and business objectives.
    • Lead, coach, and develop a team of Senior Analytics Engineers, fostering a high-performing, inclusive, and growth-oriented culture.
    • Act as a force multiplier across the group: identifying and removing structural blockers, elevating engineering standards, and scaling delivery capacity.
    • Drive and champion best practices in analytics engineering, data modelling, data governance, and operational excellence across all teams.
  • Stakeholder Management
    • Serve as the senior Engineering representative for Analytics Engineering with cross-functional leaders in Product, Finance, Sales, Marketing, and Data Platform.
    • Build and maintain trusted, long-term relationships with stakeholders at Director and VP level, proactively aligning on goals, managing expectations, and communicating progress and risk with clarity and transparency.
    • Navigate competing priorities across multiple senior stakeholders; make and communicate clear, well-reasoned trade-off decisions that reflect both engineering and business considerations.
    • Represent Analytics Engineering in Engineering leadership forums and contribute to shaping the broader engineering organisation.
    • Advocate effectively for investment (headcount, tooling, infrastructure) by constructing well-evidenced business cases and presenting them to senior leadership.
  • Data as a Product
    • Champion a product mindset for data across the organisation: ensuring Paddle's analytics data estate is treated as a first-class product with clear ownership, defined consumers, and measurable quality standards.
    • Lead the definition and governance of shared data definitions and business metrics, working cross-functionally to drive alignment and eliminate ambiguity across teams.
    • Ensure all data assets are well documented, well understood, and readily discoverable, including via MCP tooling, so that engineers, analysts, and business stakeholders can self-serve with confidence.
    • Define and enforce clear data ownership across the analytics estate, ensuring every dataset and model has an accountable team and a well-understood purpose.
    • Establish and continuously improve data quality standards: defining what 'good' looks like, instrumenting quality checks throughout the pipeline, and ensuring issues are surfaced, triaged, and resolved systematically.
    • Own the prioritisation of the Analytics Engineering roadmap, balancing strategic data product initiatives, platform reliability, data quality improvements, and stakeholder requests in a structured and transparent way.
    • Build and maintain the processes by which new data needs are brought into engineering, evaluated, and sequenced, ensuring the group can absorb demand predictably and say no clearly when needed.
  • Technical Oversight
    • Oversee the reliability, scalability, and accuracy of Paddle's analytics data estate, including core data pipelines, data models, and transformation layers (Snowflake, DBT, Fivetran).
    • Set the architectural direction for the group, guiding the most significant technical decisions and ensuring the analytics platform can scale with Paddle's growth.
    • Maintain high standards of data governance, data quality, and documentation across the group.
  • People Development
    • Create and maintain a culture of continuous learning within the group, ensuring Senior Analytics Engineers are growing in both technical depth and professional skills.
    • Provide regular, high-quality feedback, set clear growth expectations, and identify high-potential individuals early.
    • Create and maintain training resources, onboarding pathways, and knowledge-sharing rituals that systematically elevate the capability of the group.
    • Actively identify skill gaps across the group and develop plans to address them through hiring, mentoring, or targeted development initiatives.

We'd love to hear from you if you are:

  • Have significant experience leading teams of senior engineers, with a track record of building and scaling high-performing analytics engineering groups.
  • Can demonstrate strategic ownership of a technical domain: setting direction, driving alignment, and delivering measurable outcomes at group or department level.
  • Have a strong product mindset for data: you think about data assets in terms of consumers, quality, ownership, and discoverability, not just pipelines and models.
  • Are an exceptional communicator with proven senior stakeholder management skills, including the ability to influence without authority, manage competing priorities transparently, and turn complex technical context into clear business language.
  • Have deep expertise in modern analytics engineering (DBT, Snowflake, Fivetran or equivalent) and can provide strong technical oversight without being hands-on day-to-day.
  • Take a structured, principled approach to data governance: you have experience driving alignment on definitions, establishing ownership frameworks, and raising the bar on data quality at scale.
  • Are familiar with AI coding assistants (such as GitHub Copilot, Cursor, or similar) and understand how they can meaningfully improve engineering productivity within an analytics engineering context.
  • Have a working knowledge of semantic layers (such as dbt Semantic Layer, Cube, or LookML) and understand how they underpin reliable, consistent data access, including their role in enabling AI tooling and MCP-based data discoverability.
  • Are passionate about developing people and building systems, processes, and cultures that enable others to do their best work.
  • Are proactive, self-aware, and continuously looking for ways to improve both yourself and the organisation around you.

Everyone is welcome at Paddle

At Paddle, we’re committed to removing invisible barriers, both for our customers and within our own teams. We recognise and celebrate that every Paddler is unique and we welcome every individual perspective. As an inclusive employer we don’t care if, or where, you studied, what you look like or where you’re from. We’re more interested in your craft, curiosity, passion for learning and what you’ll add to our culture. We encourage you to apply even if you don’t match every part of the job ad, especially if you’re part of an underrepresented group. Please let us know if there’s anything we can do to better support you through the application process and in the workplace. We will do everything we can to support any accommodations needed. We’re committed to building a diverse team where everyone feels safe to be their authentic self. Let’s grow together.

Our Values

  • Paddle Together - “None of us, is as smart as all of us”
  • Paddle Simply - “Simple can be harder than complex: you have to get your thinking clean to make it simple”
  • Paddle for others - “We can realise our wildest dreams, so long as we help enough other people to realise theirs”

Why you’ll love working at Paddle

We are a diverse, growing group of Paddlers across the globe who pride ourselves on our transparent, collaborative and respectful culture. We are a ‘digital-first’ company, which means you can work remotely, from one of our stylish hubs, or even a bit of both! We offer all team members unlimited holidays and 4 months paid family leave regardless of gender. We invest in learning and will help you with your personal development via constant exposure to new challenges, an annual learning fund, and regular internal and external training.

Head of Analytics Engineering employer: Paddle

Paddle is an exceptional employer that fosters a transparent, collaborative, and inclusive culture, making it an ideal place for the Head of Analytics Engineering role. With the flexibility of remote work or stylish hubs, unlimited holidays, and generous family leave, Paddle prioritises employee well-being and growth. The company invests in continuous learning and development, ensuring that every team member has the opportunity to thrive and contribute meaningfully to the organisation's success.

Paddle

Contact Details:

Paddle Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Head of Analytics Engineering

Tip Number 1

Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can open doors that a CV just can't.

Tip Number 2

Prepare for interviews by researching Paddle's culture and values. Show us how you align with our mission and how you can contribute to our team!

Tip Number 3

Practice your storytelling skills. Be ready to share your past experiences in a way that highlights your achievements and how they relate to the role.

Tip Number 4

Don’t forget to follow up after interviews! A quick thank-you note can leave a lasting impression and show us you're genuinely interested in joining Paddle.

We think you need these skills to ace Head of Analytics Engineering

Leadership
Team Development
Stakeholder Management
Data Governance
Data Quality Assurance
Analytics Engineering
Technical Oversight

Some tips for your application 🫡

Tailor Your Application:Make sure to customise your CV and cover letter for the Head of Analytics Engineering role. Highlight your experience in leading teams and driving data solutions that align with Paddle's objectives. We want to see how your skills fit into our vision!

Showcase Your Communication Skills:Since this role involves a lot of stakeholder management, it's crucial to demonstrate your ability to communicate complex ideas clearly. Use examples from your past experiences where you’ve successfully influenced decisions or managed competing priorities.

Highlight Your Technical Expertise:Don’t forget to mention your hands-on experience with analytics engineering tools like DBT, Snowflake, and Fivetran. We’re looking for someone who can provide strong technical oversight, so make sure to showcase your knowledge in these areas.

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, we love seeing applications come in through our own platform!

How to prepare for a job interview at Paddle

Know Your Analytics Engineering Stuff

Make sure you brush up on your knowledge of modern analytics engineering tools like DBT, Snowflake, and Fivetran. Be ready to discuss how you've used these technologies in past roles and how they can be applied at Paddle to drive data quality and governance.

Show Off Your Leadership Skills

Prepare examples that showcase your experience in leading and developing high-performing teams. Think about specific instances where you've fostered a growth-oriented culture or removed blockers for your team. Paddle values collaboration, so highlight how you've worked with cross-functional teams.

Communicate Clearly and Confidently

Practice explaining complex technical concepts in simple terms. You’ll need to communicate effectively with stakeholders at various levels, so think about how you can turn technical jargon into clear business language. This will demonstrate your ability to influence without authority.

Emphasise Your Product Mindset

Be prepared to discuss how you view data as a product. Talk about your approach to ensuring data ownership, quality, and discoverability. Paddle is looking for someone who can champion a product mindset for data, so share your thoughts on how to treat analytics data as a first-class product.