Staff Analytics Engineer

Location

Barcelona Employment Type

Full time Location Type

Hybrid Department

Data 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 general 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 Go

📌 Staff Analytics Engineer Location: Barcelona
🏢 Preply
📍 Barcelona