Data Engineer

What You’ll Do:

• Design, build, and maintain robust data models, tables, and views in our analytics data warehouse (using dbt/Snowflake) to support product and operational analytics.
• Develop and automate analytics-layer data pipelines and ensure data quality with appropriate testing and monitoring.
• Partner with product managers, engineers, and business stakeholders to understand requirements, translate business needs into data solutions, and help define and track key metrics.
• Deliver thoughtful analyses on large, complex datasets to uncover actionable insights for product and operations improvement.
• Develop and maintain dashboards and reports in Thoughtspot to monitor KPIs, product usage, and operational performance.
• Consolidate and harmonize data across different business units and acquisitions, ensuring consistent and reliable data definitions for reporting.
• Work directly with our in-house AI platform, supporting or developing new tools to boost analytics and automation capabilities.
• Contribute to documentation and training for business users to support self-service access to data tools and reporting.
• Identify and implement opportunities to streamline and automate analytics workflows and processes in partnership with the broader team.
• Primarily work on-site 3-4 days per week as part of our collaborative Product Strategy and Analysis team.

What We’re Looking For:

• 2-3+ years of relevant experience in data engineering, analytics engineering, or advanced data analytics roles, ideally supporting product or operational analytics.
• Advanced proficiency in SQL and experience with data modeling, dbt, and cloud data warehouses (Snowflake preferred).
• Experience developing analytics-layer data pipelines, tables, and views, and ensuring data quality for reporting and analysis.
• Hands-on experience with BI/data visualization tools (Thoughtspot preferred), including dashboard/report development and self-service enablement.
• Experience analyzing complex, high-volume datasets and delivering clear, actionable insights.
• Hands-on experience with Python for data analysis and/or to interact with platforms or AI tools; prompt/AI development is a plus.
• Effective written and verbal communication skills, with the ability to convey technical information to cross-functional partners.
• Collaborative mindset and ability to thrive within a hybrid team, working on-site 3-4 days per week.

Nice to Have:

• Experience experimentation frameworks, or statistical analysis (e.g., regression, significance testing).
• Experience working in a product-centric team or fast-paced environment.
• Stakeholder management experience, especially with Product, Engineering, and Operations teams.
• Familiarity with engineering best practices (versioning, testing, monitoring)