preply - Senior Analytics Engineer
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Requirements
• 5+ years of hands-on experience in analytics engineering, data engineering, or related fields. • Expert proficiency in SQL and Python, with a proven track record in designing, implementing, and optimizing data models. • Deep understanding of advanced data governance frameworks, modeling best practices, and implementation of scalable self-service analytics platforms. • Proven track record in identifying complex problems and delivering proactive, innovative solutions to uncover new use cases of our data to bring direct business impact. • Strategic mindset, high creativity, and an initiative-driven approach to developing and evaluating cutting-edge solutions. • Fluency in English (C1 level or above), with exceptional ability to clearly articulate complex data concepts to diverse stakeholders. • Experience leading and scaling data infrastructure within rapidly growing startups. • Advanced hands-on expertise with DBT, Looker, or Airflow. • Proven experience in defining and standardizing event taxonomies and KPIs within medium-to-large organizations. • Strong experience in AWS or Google Cloud data ecosystems.
Responsibilities
• Lead the architecture, design, and evolution of complex data models ensuring clarity, accessibility, scalability, and reliability. • Develop and optimize sophisticated ETL/ELT pipelines, enhancing performance and scalability within our multi-terabyte data ecosystem. • Own and enhance our BI layer (Looker via LookML), ensuring intuitive, performant, and scalable self-service analytics. • Provide technical leadership in collaboration with data science teams to optimize analytical workflows, reduce redundancy, and enforce robust data governance. • Champion engineering best practices, including advanced version control, CI/CD pipelines for analytics, and rigorous automated data quality monitoring. • Drive initiatives ensuring data reliability, cleanliness, accuracy, and comprehensive documentation for critical business decision-making. • Strategically influence and drive company-wide data strategies supporting rapid product growth, sophisticated experimentation, and large-scale personalization initiatives.
Benefits
• 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. • An open, collaborative, dynamic and diverse culture; • A generous monthly allowance for lessons on Preply.com http://preply.com, Learning & Development budget and time off for your self-development; • A competitive financial package with equity, leave allowance and health insurance; • Access to free mental health support platforms;
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