Senior Analytics Engineer
WFA Digital Insight
Vanta’s Senior Analytics Engineer sits at the intersection of data engineering and product insight, tasked with turning raw security telemetry into actionable dashboards and AI‑ready datasets. Unlike generic analytics roles, Vanta expects you to shape the entire analytics stack—from dbt‑driven modeling to Snowflake performance tuning—while collaborating directly with data scientists and product engineers. The position also calls for a software‑engineering mindset, meaning you’ll write reusable frameworks rather than one‑off queries, and you’ll help expose data through front‑end tools for enterprise‑wide consumption. Candidates who thrive here enjoy a remote‑first culture, a strong emphasis on developer experience, and the chance to influence security‑focused data practices across a fast‑growing tech company.
Job Description
At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. As a Senior Analytics Engineer, you’ll be responsible for laying the foundation for a best-in-class analytics function. You’ll partner closely with our data science team and business stakeholders to ensure that our analytics stack and processes meet the business needs today with an eye towards the future. What you’ll do as an Senior Analytics Engineer at Vanta: - Design and implement complex data models to enable dashboards, self-serve analytics, and data science teams.
- Write highly tuned, scalable SQL queries running over large-scale, heterogeneous data warehouses.
- Enable AI tooling with semantic layers and observability, guiding analytics functions on best practices.
- Manage and improve data infrastructure needed to drive data-driven decision-making solutions.
- Help develop front end applications to expose analytical data sets enterprise wide - Work with the Product and Corporate Engineering system teams to structure source systems for reporting consumption across the enterprise.
- Have experience with common analytics tooling (e.g. dbt is a must, Stitch/Fivetran, Snowflake/BigQuery/Redshift, Airflow, Dagster, Looker/Mode/Sigma).
- Bring a system-oriented and software engineering mindset to the Analytics Engineering practice.
- Deep knowledge of crafting dimensional and fact models in modern data fashion.
- Have a passion for enabling the developer experience of data, and being obsessed with giving data super powers across the company.
- Desire to lead the industry in security, anonymization, and compliance management when it comes to data warehousing.
- Must be authorized to work in the U.S. without the need for current or future employer sponsorship.
- Open to using AI to amplify their skills and strengthen their work - demonstrating curiosity, a willingness to learn, and sound judgment in applying AI responsibly to improve efficiency and impact.
- Offices in SF, NYC, London, Dublin, Tel Aviv, and Sydney To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state.
How to Stand Out
- Highlight any production‑grade dbt projects in your resume; include links to GitHub repos or documentation.
- Prepare a short case study of a complex SQL optimization you performed, focusing on performance gains.
- Demonstrate familiarity with Vanta’s tech stack (Snowflake/BigQuery, Airflow/Dagster) by mentioning relevant hands‑on experience.
- During interviews, discuss how you would build reusable data models to reduce ad‑hoc query churn.
- Emphasize any experience with security or compliance data, as Vanta values that domain knowledge.
- When negotiating, reference the equity component and remote‑work stipends as part of the total compensation.
- Watch for any requirement that you must be U.S. authorized without sponsorship; ensure you meet this before proceeding.
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