Senior Analytics Engineer
1password
| Company | 1password |
| Category | Engineering |
| Location | Remote (United States | Canada) |
| Remote | Remote |
| Employment | Not stated |
| Level | Senior |
| Salary | Not stated by the employer |
| Posted | 15 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (ashby) |
Description
1Password is growing. We’ve surpassed $400M in ARR and we’re continuing to accelerate, earning a spot on the Forbes Cloud 100 for four years in a row and teaming up with iconic partners like Oracle Red Bull Racing.
About 1Password
At 1Password, we’re building the foundation for a safe, productive digital future. Our mission is to unleash employee productivity without compromising security by ensuring every identity is authentic, every application sign-in is secure, and every device is trusted. We innovated the market-leading enterprise password manager and pioneered Unified Access Management, a new cybersecurity category built for the way people and AI agents work today. As one of the most loved brands in cybersecurity, we take a human-centric approach in everything from product strategy to user experience. Over 180,000 businesses, from Fortune 100 leaders to the world’s most innovative AI companies, trust 1Password to help their teams securely adopt the SaaS and AI tools they need to do their best work.
If you're excited about the opportunity to contribute to the digital safety of millions, to work alongside a team of curious, driven individuals, and to solve hard problems in a fast-paced, dynamic environment, then we want to hear from you. Come join us and help shape a safer, simpler digital future.
We are looking for a Senior Analytics Engineer to join the Analytics & Data Engineering team. You will work at the intersection of data engineering and analytics, partnering with analysts and stakeholders across the business—including Product, Finance, GTM, and Marketing—to turn raw data into trusted, reusable datasets. Our team powers reporting, ad-hoc analysis, data science, and increasingly, AI analytics workloads. On a typical day you will model data from a broad ecosystem of sources on our central data platform, help define and validate key metrics, and ensure the data our models, dashboards, and AI tools depend on is accurate, reliable, and well documented. As AI capabilities become central to how we operate and serve customers, the data foundations you build will directly enable those systems to function at their best.
How we’re using AI today
Our Engineering, Product, and Design teams are thoughtfully integrating AI across the full software and product development lifecycle to move faster without sacrificing quality or security. In practice, that looks like engineers using AI-assisted coding tools to accelerate reviews and catch bugs earlier, product managers synthesizing user research at scale, and designers rapidly prototyping and iterating with AI-generated mockups. We approach AI the same way we approach security: with clear principles, human accountability at every consequential decision point, and rigorous evaluation before anything ships to customers.
This is a remote opportunity within Canada and the US.
What we're looking for:
- 5+ years in analytics or data engineering, with 3+ years focused on analytics engineering and production DBT development
- Expert-level SQL and DBT skills, including advanced modeling patterns, incremental processing, and multi-environment deployment
- Deep experience with modern cloud data warehouses (e.g. Athena, Snowflake, BigQuery, Databricks, or Redshift), including performance tuning, partitioning, and incremental strategies
- Strong understanding of dimensional modeling, metric design, and how to document grains and business logic for consumers
- Familiarity with semantic layer or metrics tooling (e.g. LookML, MetricFlow, dbt Semantic Layer) or equivalent in-repo metric standards
- Hands-on experience with CI/CD for data pipelines and orchestration tools (e.g. Airflow, Dagster, Prefect)
- Able to communicate complex data concepts clearly to both technical and non-technical audiences
Bonus points for:
- Experience with B2B SaaS metrics (subscription revenue, customer lifecycle, usage and adoption)
- Event-stream or behavioural data
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