As a Senior Analytics Engineer at dbt Labs, you will be part of a team building the foundation to scale analytics across our Go-To-Market (GTM) and Product teams. You will collaborate with key stakeholders to build scalable solutions to transform data into key metrics reporting and insights. You will be responsible for ensuring teams have access to reliable, accurate metrics that can scale with our company's growth. You will also lead your own projects to enable self-serve insights to help teams make data-driven decisions.
This is a critical role for the organization and requires an individual with effective communication skills, outstanding business acumen, and the ability to work across various functional teams and internal partner teams. We are looking for individuals who are self-starters comfortable with ambiguity, demonstrate strong attention to detail, and have the ability to work in a fast-paced and ever-changing environment.
In this role, you can expect to: Understand the data needs of GTM and Product teams in terms of key data models and reporting, and translate that into technical requirements. Own our dbt instance, defining and maintaining key data pipelines and charts that power core company-wide metrics. Establish high data integrity standards and SLAs to ensure timely, accurate delivery of data. Develop canonical datasets to track key product metrics including user growth, engagement, and revenue. Build insightful and reliable dashboards to track performance of core metrics that will deliver insights to the whole company. Build foundational data products and tools to enable self-serve analytics to scale across the company. Influence the future roadmap of Product and GTM teams from a data systems perspective. Become an expert in our GTM and Product data models and the company's data architecture. You are a good fit if you have: Worked asynchronously as part of a fully-remote, distributed team. Excellent communication skills to convey complex technical concepts to non-technical stakeholders. Have 4+ years of experience as an Analytics Engineer or similar Data Science & Analytics roles, preferably partnering with GTM and Product leads to build and report on key company-wide metrics. Expertise in SQL and Python to transform data into accurate, clean data models. Expertise in building multi-step ETL jobs through tooling like dbt and orchestrated through workflow management platforms like Prefect. Experience building data reporting and dashboarding in visualization tools to serve multiple cross-functional teams. A bias for action and urgency, not letting perfect be the enemy of the effective. A "full-stack mindset", not hesitating to do what it takes to solve a problem end-to-end, even it it requires going outside the original job description. You'll have an edge if you have: Experience developing and scaling a dbt project while leveraging engineering best practices (e.g. data quality tests, unit tests, etc). Have experience at a SaaS company. What to expect in the hiring process (all video interviews unless accommodations are needed): Interview with Talent Acquisition Partner Interview with Hiring Manager Team Interviews #J-18808-Ljbffr
