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Staff Analytics Engineer

Pay
Pay not listed
Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Data — team source

What you’ll work on

Full posting
  • Lead design of core analytical data models across key business domains

  • Define analytics engineering standards for modeling, naming, testing and docs

  • Build and optimize ETL/ELT pipelines for multi-terabyte data volumes

  • Own and evolve the Looker semantic layer for self-service analytics

  • Mentor and guide analytics engineers through reviews and architecture advice

From the employer’s posting
Lead the design and evolution of core analytical data models across key business domains
Define and champion analytics engineering standards (modeling patterns, naming conventions, testing strategies, documentation)
Build and optimize robust ETL/ELT pipelines that handle multi-terabyte data volumes
Own and evolve our BI and semantic layer (Looker / LookML), enabling intuitive, performant, and truly self-service analytics
Act as a technical leader and mentor within the Analytics Engineering discipline, raising the bar through example, reviews, and architectural guidance
Apply at Preply

Posting record

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Open 5 monthsWe first saw this posting 155 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Jun 2, 2026155 days ago
Recorded sightings
271
Last seen by us
Nov 4, 2026
Employer says posted
Feb 2, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 155

Up longer than most. Similar jobs usually come down between day 6 and day 47.

Well past Preply’s usual: its jobs come down by about day 38.

From 1,417 similar postings that came down, and 16 of Preply’s. Coming down is not always a hire.

Preply is hiring

23 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring is picking up
  • Its jobs tend to stay up a long time
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • dbt
  • Looker
  • Airflow
  • GCP
Where the posting names them
- 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).

Your next step

Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.

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  • No account needed. “Autofill from resume” at the top of the form fills the key fields from your file.

Already applied? Track this application

Has Preply posted this job before?

Yes. We’ve followed 2 other Staff Analytics Engineer jobs there since June 2026. All 2 are still up.

  1. LondonStill up after 156 days, first seen Jun 2
  2. BarcelonaStill up after 156 days, first seen Jun 2
  3. This jobUp 156 days so far, first seen Jun 2

About the role

We file this job under Analytics Engineer, by the work the posting describes.

Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.

Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.

A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

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.

    #LI-VL1

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.

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Kyiv, Ukraine

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