LandOffer
Data Analyst
Job details
- Experience
- 3+ years
- Education
- Bachelor's degree
- Posted
- Nov 2, 2026
- Last confirmed open
- Nov 2, 2026
About this role
About The Role
The role sits at the intersection of data engineering and business strategy, turning raw product and operational data into analyses that drive roadmap and revenue decisions. You will work directly with product managers, finance, and leadership, owning the analytics layer on top of a modern warehouse stack — dbt models, dashboards, and self-serve reporting used across the company.
Key Responsibilities
Design, build, and maintain dbt models and SQL transformations on a Snowflake warehouse, ensuring data accuracy and clear documentation Develop and own dashboards in Looker (or Tableau) used by leadership for weekly business reviews and product decision-making Run deep-dive analyses on activation, retention, and monetization funnels, translating findings into concrete product recommendations Partner with data engineers to improve pipeline reliability, data contracts, and source system ingestion quality Define and instrument product metrics, maintaining a trusted semantic layer shared across teams Communicate insights clearly to non-technical stakeholders through written analyses and executive summaries Mentor junior analysts and contribute to analytics standards, testing practices, and code review culture What We Are Looking For 3–6 years of experience in data analytics, analytics engineering, or a comparable role at a product-driven tech company Advanced SQL skills: window functions, CTEs, query optimization on large datasets Hands-on experience with dbt and a cloud data warehouse (Snowflake, BigQuery, or Redshift) Proficiency in Python or R for analysis, with comfort using pandas for ad hoc and production workflows Experience building dashboards in Looker, Tableau, or Power BI, including semantic modeling Bachelor's degree in a quantitative field (statistics, economics, computer science) or equivalent practical experience Bonus: experience with experimentation/A-B testing frameworks, airflow, or event data tooling (Segment, Amplitude)