Вакансия Analytics Engineer

Skills

• SQL
• Python
• dbt
• Looker
• Apache Airflow
• AWS
• GCP
• Luigi
• Jenkins

Описание вакансии

At Preply, we run hundreds of A/B tests at any given time, each with unique tracking and analytical challenges. Our platform spans a diverse product ecosystem, with sophisticated tutor-learner interactions that generate a vast amount of data. This creates an exciting, high-impact environment where data engineering plays a crucial role in shaping our business decisions.
We are passionate about building a modern data infrastructure that enables our teams to extract insights, optimize experiments, and power innovation. As Analytics Engineer, you will help shape critical data models, streamline pipelines, and optimize our analytics stack to empower decision-making across the company.

Why You’ll Love This Role:

• Cutting-edge data stack: work with DBT, Snowflake, Airflow, Looker, Databricks, Monte Carlo, and help shape our future tech choices.
• End-to-End impact: own and evolve the entire data pipeline, from ingestion to transformation and modeling, ensuring accuracy, scalability, and performance.
• Cross-team collaboration: partner with data scientists, analysts, and engineers to create high-quality, actionable datasets for business insights.
• Continuous learning & growth: be part of a data-driven culture where innovation, best practices, and ownership drive success.

What You’ll Be Doing:

• Design, build, and evolve our data models to ensure simplicity, accessibility, scalability, and reliability.
• Develop efficient ETL/ELT pipelines, optimizing event ingestion and transformation across our multi-terabyte data lake/warehouse.
• Optimize and manage our BI layer (Looker via LookML), ensuring clear, intuitive, and performant self-service analytics.
• Collaborate with data scientists to optimize pipelines, minimize redundancies, and improve data governance.
• Apply software engineering best practices like version control, CI/CD for analytics, and automated data quality checks.
• Drive data reliability initiatives, ensuring clean, accurate, and well-documented data for decision-making.
• Influence company-wide data strategies to support product growth, experimentation, and personalization at scale.

What you need to succeed:

• Around 3-5 years of experience in analytics engineering, data engineering, or similar roles.
• Proficiency in SQL and Python. Experience building and maintaining BI models.
• A strong understanding of data governance, modeling best practices, and self-service analytics.
• A rare combination of technical skills, business mindset and communication skills, able to persuade and influence data/business stakeholders;
• Strong curiosity, problem-finding and problem-solving skills;
• Creative mindset and a proactive/can-do attitude towards the creation and evaluation of new solutions;
• Fluency in English (C1 level or above), with the ability to communicate complex data concepts clearly.

Nice to have:

• Experience scaling data infrastructure in fast-growing startups.
• Hands-on experience with DBT, Looker, or Airflow.
• Knowledge of event taxonomy standardization and KPI definition across medium-to-large organizations.
• Experience working with AWS or Google Cloud data ecosystems.
• Familiarity with other workflow orchestration tools (Luigi, Jenkins, etc.).