Analytics Engineer

Preply creates learning experiences that help people find tutors, build personalized learning journeys, and stay motivated. Its human-led, technology-enabled approach supports more than 100,000 tutors teaching over 90 languages to learners in 180 countries.

• Lead the design and evolution of core analytical data models across key business domains, ensuring clarity, scalability, and long-term sustainability
• Define and champion organization-wide analytics engineering standards for modeling patterns, naming conventions, testing strategies, and documentation
• Build and optimize reliable, high-performance ETL/ELT pipelines handling multi-terabyte data volumes
• Own and evolve the BI and semantic layer using Looker / LookML to enable intuitive, performant, self-service analytics
• Partner with Data Scientists, Product Managers, and Engineers to streamline analytical workflows and reduce duplicated logic (SSOT)
• Drive data quality, reliability, and governance initiatives, ensuring decision-critical datasets are trustworthy and well-documented
• Influence company-wide data strategy for product experimentation, marketplace growth, and large-scale personalization
• Work with the engineering team to provide data products for Experimentation, Engineering, and Applied AI teams
• Provide technical leadership and mentorship in Analytics Engineering through example, reviews, and architectural guidance

• Extensive experience in analytics engineering, data engineering, or related roles working with complex, high-impact data systems
• Expert-level SQL proficiency and experience using Python in data workflows
• Proven track record designing scalable analytical data models for 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 and ability to turn ambiguous problems into clear, data-backed solutions
• Exceptional communication skills and ability to influence and align technical and non-technical stakeholders
• Proactive, strategic mindset focused on improving systems, standards, and long-term outcomes
• Fluent English (C1 or above)
• Будет плюсом: experience scaling data platforms in high-growth or post-Series C startups, defining and standardizing event taxonomies, KPIs, and canonical metrics, experience with AWS or Google Cloud data ecosystems, mentoring or coaching data professionals

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