Senior Engineering Manager (Data Platform)

Description

We power people’s progress.

At the company, we’re all about creating life-changing learning experiences. We help people discover the magic of the perfect tutor, craft a personalised learning journey, and stay motivated to keep growing. Our approach is human-led, tech-enabled - and it’s creating real impact.

As a category-defining company, we’re shaping what the future of learning looks like at global scale.

Every the company lesson sparks change, fuels ambition, and drives progress that matters. Joining the company means helping define the future of education at global scale, and building something that truly matters for millions of people, every day.

Meet the team!

At the company, the Data Platform team provides a single, trusted, and scalable data foundation for the whole company. The team ensures that all analytics, machine learning, and product features are built on unified, governed, and production-grade data assets in the company's Lakehouse — including the extraction, normalization, and generation of structured data from the company's unstructured assets, forming a durable data moat for AI-driven products.

The team owns end-to-end batch and streaming ingestion pipelines, data contracts and quality checks, enrichment and modeling across domains, and the self-service tooling that lets other teams onboard new data sources within clear guardrails. It works closely with ML Platform, Applied and Data Scientists, Analytics Engineering, Backend, and Product squads, so that datasets, features, and pipelines are production-ready, observable, and reusable across the company.

As the Senior Engineering Manager for Data Platform, you'll own the engineering strategy, execution, and organizational health of the team that every analytics, ML, and AI initiative at the company depends on. This is a leadership role for a manager with strong technical judgment. You'll go deep on data architecture, reliability, and platform abstractions, coach senior engineers, set operational standards, and partner with Data, ML, Product, Security, and Engineering leaders across the company.

We've reached 90%+ adoption of AI coding tools across engineering, and are now moving towards more autonomous, AI-augmented development at scale. As an Engineering Manager, you’ll help your team adopt these ways of working while setting the right standards and guardrails.

Learn more about how we build on our Engineering Blog , Tech Radar , and YouTube channel !

What you'll be doing:

Lead and grow a high-performing data engineering team, fostering a culture of ownership, continuous improvement, and technical excellence.

Coach and develop engineers, support them through regular feedback, mentorship, and career development, while creating an inclusive and collaborative team environment.

Define and drive the long-term vision for the company's data foundation — the Lakehouse, ingestion layers, data contracts, enrichment , and governance — ensuring alignment with company objectives and the needs of analytics, ML, and product teams.

Identify and prioritize high-impact opportunities, partner closely with Analytics, ML Platform, Data Science, and Product to ensure the team focuses on the datasets, pipelines, and tooling that deliver the greatest customer and business value.

Own execution and delivery. Translate strategy into realistic plans, balancing foundational platform investment with near-term needs of consuming teams while surfacing trade-offs and maintaining speed, quality, cost efficiency, and predictability.

Provide technical leadership, guide architecture across batch and streaming ingestion, data modeling, quality, and governance; help the team navigate trade-offs and remove technical obstacles.

Own data reliability and trust. Establish SLOs, observability, and incident response for data pipelines, moving the platform from reactive firefighting to proactive reliability management.

Champion engineering best practices. Drive continuous improvements in code quality, operational excellence, development processes, and technology evolution.

Collaborate cross-functionally, work with stakeholders across the broader business to maximize impact and align on priorities, data ownership, standards, and outcomes.

Own hiring quality, team composition, and operating model, evolving team boundaries as the platform and company needs change.

What you need to succeed

8+ years of software or data engineering experience , including 5+ years in engineering management, with experience leading data or platform engineering teams.

People-centric approach and team-building skills : a passion for building high-performing teams and helping people grow. You know how to create alignment, foster psychological safety, provide actionable feedback, and develop engineers through coaching and mentorship.

Strong technical judgment and systems thinking. You are comfortable driving architectural discussions, evaluating technical trade-offs, championing engineering best practices, and partnering with senior engineers on technical strategy.

A track record of hiring , coaching, and retaining high-performing teams, including senior engineers.

Product & Business Partnership : You're comfortable working closely with Analytics, Data Science, ML, and Product partners to identify opportunities, prioritize investments, and drive measurable outcomes. You naturally connect data platform decisions to downstream user experience, business metrics, and company strategy.

Clear communication and stakeholder leadership , with the ability to align teams with different incentives, make sound decisions with incomplete information, and revisit assumptions as the data ecosystem changes.

Results-Oriented : A track record of driving performance. You know how to motivate teams to set and achieve ambitious, business-focused, and measurable goals.

Ethical Leadership : You lead by example, serving as the team's moral compass by demonstrating empathy, transparency, accountability, and a strong sense of ownership. You value honesty and fairness, creating a culture where people feel safe to challenge ideas, learn, and grow.

Requirements

• Hands-on familiarity with the modern data stack — for example, Spark, Flink, Kafka, Debezium, Airflow, dbt, or similar — and with cloud platforms (AWS/GCP or equivalent) and modern DevOps practices.
• Experience running a data platform as a product: data contracts, self-service onboarding, discoverability, and measuring success through adoption and consumer outcomes.
• Experience with data governance, privacy, and compliance at ingestion time (classification, access control, masking, auditability).
• Familiarity with feature stores, ML data pipelines, or preparing data for GenAI / RAG use cases.
• AI Expertise: You use Agentic AI beyond code generation to support architecture, planning, and decision-making, while retaining human judgment for architecture, people decisions, business logic, and security, and establishing quality gates and safety nets for team workflows.
• Why you’ll love it at the company:
• An open, collaborative, dynamic, and diverse culture;
• A generous monthly allowance for lessons on the company's site , Learning & Development budget, and time off for your self-development;
• A competitive financial package with equity, leave allowance and health insurance;
• Access to free mental health support platforms;
• Access to Gympass-partnered wellness and gym centers throughout London to promote and support well-being and physical health;
• Our Principles
• Care to change the world - We are passionate about our work and care deeply about its impact to be life changing.
• We do it for learners - For both the company and tutors, learners are why we do what we do. Every day we focus on empowering tutors to deliver an exceptional learning experience.
• Keep perfecting - To create an outstanding customer experience, we focus on simplicity, smoothness, and enjoyment, continually perfecting it as every detail matters.
• Now is the time - In a fast-paced world, it matters how quickly we act. Now is the time to make great things happen.
• Disciplined execution - What makes us disciplined is the excellence in our execution. We set clear goals, focus on what matters, and utilize our resources efficiently.
• Dive deep - We leverage business acumen and curiosity to investigate disparities between numbers and stories, unlocking meaningful insights to guide our decisions.
• Growth mindset - We proactively seek growth opportunities and believe today's best performance becomes tomorrow's starting point. We humbly embrace feedback and learn from setbacks.
• Raise the bar - We raise our performance standards continuously, alongside each new hire and promotion. We build diverse and high-performing teams that can make a real difference.
• Challenge, disagree and commit - We value open and candid communication, even when we don’t fully agree. We speak our minds, challenge when necessary, and fully commit to decisions once made.
• One the company - We prioritize collaboration, inclusion, and the success of our team over personal ambitions. Together, we support and celebrate each other's progress.