9 months ago
Kyiv, UkraineStaff+
Responsibilities
- Lead the design and evolution of scalable analytical data models across key business domains.
- Define and champion organization-wide analytics engineering standards, including modeling patterns, naming conventions, testing strategies, and documentation.
- Build and optimize reliable ETL/ELT pipelines for multi-terabyte data volumes.
- Own and evolve the Looker and LookML BI and semantic layer for performant self-service analytics.
- Partner with Data Scientists, Product Managers, and Engineers to streamline analytical workflows and reduce duplicated logic.
- Drive data quality, reliability, governance, and documentation initiatives for decision-critical datasets.
- Influence company-wide data strategy supporting experimentation, marketplace growth, and large-scale personalization.
- Provide data products for Experimentation, Engineering, and Applied AI teams.
- Mentor analytics engineers and provide technical reviews, architectural guidance, and discipline-wide leadership.
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.
- A 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, analytics architecture, and self-service BI platforms.
- Strong business acumen and the ability to translate ambiguous problems into data-backed solutions.
- Exceptional communication and stakeholder-influence skills across technical and non-technical teams.
- A proactive and strategic mindset focused on improving systems, standards, and long-term outcomes.
- Fluency in English at C1 level or above.
- Experience scaling data platforms in high-growth or post-Series C startups is preferred.
- Experience defining and standardizing event taxonomies, KPIs, and canonical metrics is preferred.
- Strong experience with AWS or Google Cloud data ecosystems is preferred.
- Experience mentoring or coaching other data professionals is preferred.
About Preply
Preply builds an online marketplace that connects learners with human tutors for live language lessons, supported by AI tools. Consumers book 1:1 sessions and ongoing courses, while organizations use Preply Business for corporate language training; revenue comes from commissions and subscriptions. Founded in 2012 and privately held, Preply operates globally with 100,000+ tutors teaching 90+ languages.