About Preply
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.
Responsibilities
•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
Requirements
•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)
Nice to have
•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
Conditions
No conditions stated in the posting.
