Staff Analytics Engineer
London, Greater London, United Kingdom
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
Tools in this posting
- Python
- SQL
- AWS
- dbt
- Looker
- Airflow
- Google Cloud (GCP)
Source — Tool mentions in context
- Extensive experience in analytics engineering, data engineering, or related roles, operating on complex, high-impact data systems. - Expert-level proficiency in SQL, with experience using Python in data workflows. - Proven track record of designing scalable analytical data models that support experimentation, reporting, and strategic decision-making.
- Proven experience defining and standardizing event taxonomies, KPIs, and canonical metrics. - Strong experience working with AWS or Google Cloud data ecosystems. - Previous experience mentoring or coaching other data professionals.
- Proven track record of designing scalable analytical data models that support experimentation, reporting, and strategic decision-making. - Advanced hands-on experience with dbt, Looker, Airflow, or similar tools. - Deep understanding of data modeling best practices, analytics architecture, and self-service BI platforms.
- Build and optimize robust ETL/ELT pipelines that handle multi-terabyte data volumes with high reliability and performance. - Own and evolve our BI and semantic layer (Looker / LookML), enabling intuitive, performant, and truly self-service analytics. - Partner closely with Data Scientists, Product Managers, and Engineers to streamline analytical workflows and reduce duplicated logic (SSOT).
Job description
We power people’s progress.
At Preply, 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.
We’ve just reached unicorn status with a $150M Series D, accelerating our vision to transform education through human-led, AI-enhanced learning. Today, 100,000+ tutors teach 90+ languages to learners in 180 countries - and we’re only getting started. As a category-defining company, we’re shaping what the future of learning looks like at global scale.
Every Preply lesson sparks change, fuels ambition, and drives progress that matters. Joining Preply 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 Preply, data is foundational to how we build, experiment, and scale our product. We run hundreds of A/B tests at any given time, power a complex two-sided marketplace, and increasingly rely on data to enable AI-driven personalization and decision-making.
Our analytics platform supports teams across Product, Growth, Finance, and Engineering/AI, and its quality directly impacts the speed and confidence of company-wide decisions.
As a Staff Analytics Engineer, you will play a critical role in shaping the analytical foundations of Preply. You’ll operate at a company-wide level, setting standards, designing scalable data models, and influencing how analytics engineering is practiced across teams. This is a role for someone who wants to build systems that others build on.
Our Data Team is dedicated to empowering top-quality decision-making. Do you want to know how? Visit our Tech Radar to learn about the technologies we use at Preply!
What you’ll be doing
Lead the design and evolution of core analytical data models across key business domains, ensuring clarity, scalability, and long-term sustainability.
Define and champion analytics engineering standards (modeling patterns, naming conventions, testing strategies, documentation) used across the organization.
Build and optimize robust ETL/ELT pipelines that handle multi-terabyte data volumes with high reliability and performance.
Own and evolve our BI and semantic layer (Looker / LookML), enabling intuitive, performant, and truly self-service analytics.
Partner closely with Data Scientists, Product Managers, and Engineers to streamline analytical workflows and reduce duplicated logic (SSOT).
Drive initiatives focused on data quality, reliability, and governance, ensuring decision-critical datasets are trustworthy and well-documented.
Influence company-wide data strategy to support rapid product experimentation, marketplace growth, and large-scale personalization.
Work closely with the engineering team to provide valuable data products for Experimentation, Engineering and Applied AI teams.
Act as a technical leader and mentor within the Analytics Engineering discipline, raising the bar through example, reviews, and architectural guidance.
What you need to succeed
Extensive experience in analytics engineering, data engineering, or related roles, operating on complex, high-impact data systems.
Expert-level proficiency in SQL, with experience using Python in data workflows.
Proven track record of designing scalable analytical data models that support experimentation, reporting, and strategic decision-making.
Advanced hands-on experience with dbt, Looker, Airflow, or similar tools.
Deep understanding of data modeling best practices, analytics architecture, and self-service BI platforms.
Strong business acumen, with the ability to translate ambiguous problems into clear, data-backed solutions.
Exceptional communication skills, with the ability to influence and align stakeholders across technical and non-technical teams.
A proactive, strategic mindset, you look beyond immediate tasks to improve systems, standards, and long-term outcomes.
Fluency in English (C1 level or above).
Nice to have
Experience scaling data platforms in high-growth or post-Series C startups.
Proven experience defining and standardizing event taxonomies, KPIs, and canonical metrics.
Strong experience working with AWS or Google Cloud data ecosystems.
Previous experience mentoring or coaching other data professionals.
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 Preply 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 Preply - We prioritize collaboration, inclusion, and the success of our team over personal ambitions. Together, we support and celebrate each other's progress.
Diversity, Equity, and Inclusion
Preply.com is committed to creating an inclusive environment where people of diverse backgrounds can thrive. We believe that the presence of different opinions and viewpoints is a key ingredient for our success as a multicultural Ed-Tech company. That means that Preply will consider all applications for employment without regard to race, color, religion, gender identity or expression, sexual orientation, national origin, disability, age or veteran status.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
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Source & posting history
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- Pay
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- Location & working pattern
London, Greater London, United Kingdom
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- Status in our records
- Active
- First seen by us
- Jun 2, 2026
- Recorded sightings
- 213
- Last seen by us
- Oct 7, 2026
- Employer says posted
- Feb 2, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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