Analytics Engineer: Build Scalable Metrics & Dashboards

As an Analytics Engineer, you will be an early member of the Data Science & Analytics team building the foundation to scale analytics across our GTM and Product teams. You will collaborate with key stakeholders in GTM and Product 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. Responsibilities: 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 marts that power core company-wide metrics Establish high data integrity standards and SLAs to ensure timely, accurate delivery of data 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 may be a good fit if you have: 5+ 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. A passion for the company's mission of building helpful, honest, and harmless AI Expertise in building multi-step ETL jobs through tooling like dbt and orchestrated through workflow management platforms like Airflow Expertise in SQL and Python to transform data into accurate, clean data models 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 if it requires going outside the original job description Experience building Analytics Engineering (or similar) function at start-ups A strong disposition to thrive in ambiguity, taking initiative to create clarity and forward progress Deadline to apply: None. Applications will be reviewed on a rolling basis. The expected salary range for this position is: Annual Salary: $200,000—$240,000 USD Logistics Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. US visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate; operations roles are especially difficult to support. But if we make you an offer, we will make every effort to get you into the United States, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Compensation and Benefits Anthropic’s compensation package consists of three elements: salary, equity, and benefits. We are committed to pay fairness and aim for these three elements collectively to be highly competitive with market rates. Equity - For eligible roles, equity will be a major component of the total compensation. We aim to offer higher-than-average equity compensation for a company of our size, and communicate equity amounts at the time of offer issuance. US Benefits - The following benefits are for our US-based employees: Optional equity donation matching. Comprehensive health, dental, and vision insurance for you and all your dependents. 401(k) plan with 4% matching. 22 weeks of paid parental leave. Unlimited PTO – most staff take between 4-6 weeks each year, sometimes more! Stipends for education, home office improvements, commuting, and wellness. Fertility benefits via Carrot. Daily lunches and snacks in our office. Relocation support for those moving to the Bay Area. UK Benefits - The following benefits are for our UK-based employees: Optional equity donation matching. Private health, dental, and vision insurance for you and your dependents. Pension contribution (matching 4% of your salary). 21 weeks of paid parental leave. Unlimited PTO – most staff take between 4-6 weeks each year, sometimes more! Health cash plan. Life insurance and income protection. Daily lunches and snacks in our office. This compensation and benefits information is based on Anthropic’s good faith estimate for this position as of the date of publication and may be modified in the future. Employees based outside of the UK or US will receive a different benefits package. The level of pay within the range will depend on a variety of job-related factors, including where you place on our internal performance ladders, which is based on factors including past work experience, relevant education, and performance on our interviews or in a work trial. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. #J-18808-Ljbffr