Analytics Engineer

Responsibilities:

• User Behavior Data Governance: Design, implement, develop and maintain scalable governance frameworks to ensure the accuracy, consistency, and integrity of user-event data. Collaborate cross-functionally to define tracking strategies, conduct audits, and enforce best practices
• Internal Data Tool Development: Build, test, and deploy internal data tools and dashboards using JavaScript or Python. Develop automated data pipelines, user-friendly analytics interfaces, and self-service solutions that empower business teams
• Competitive Intelligence & Data Scraping: Architect and maintain automated web-scraping systems to gather competitor insights—such as pricing, feature sets, and market trends. Ensure solutions are efficient, robust, and compliant with legal and ethical guidelines
• Machine Learning & Advanced Analytics: Apply statistical methods or machine learning models to unlock business value—such as forecasting user behavior, predicting churn, or optimizing product features
  

• Expert-level SQL and strong Python or JavaScript abilities for data transformation and tool development
• Proven experience implementing data governance or event instrumentation processes (e.g., Segment, GA4, Mixpanel)
• Data Pipeline & ETL/ELT Expertise: Track record designing and maintaining data pipelines using frameworks like dbt, Airflow, Talend, or similar
• Web Scraping Competency: Comfortable with scraping technologies and libraries, and adept at orchestrating automated scraping workflows
• Analytical & Problem-Solving Skills: Demonstrated ability to break down complex problems, translate stakeholder needs, and produce clean, documented data solutions
• Collaboration & Communication: Excellent at bridging terminology between technical and business stakeholders. Clear, concise in written and verbal communication
  
  

• Experience with cloud data warehouses (Snowflake, BigQuery, Redshift) and BI tools (Looker, Tableau)
• Familiarity with software development workflows: Git, code reviews, modular design, CI/CD
• Hands-on knowledge of machine learning libraries (scikit-learn, TensorFlow/PyTorch)
• Front-end development experience (React, Vue, Node.js) to build polished internal tools
• Awareness of data privacy, legal compliance, and ethical considerations in scraping and data governance