Data Scientist

Cape • New York, NY

21d

About The Position

Cape was founded in early 2022 by Palantir and Anduril alums with deep expertise in privacy and national security. While running Palantir’s US national security business, our CEO became passionate about privacy and security on mobile devices. Our mission is to be a force for good in global wireless.
At Cape, we are not just another cellular service provider; we are the architects of a privacy-centric movement that starts with the devices in your pocket. We are building a cellular network that helps citizens, including those responsible for our nation’s security, regain control of their own data.
We believe that where we are, where we go, and whom we are with are among our most personal information and should be kept private. Privacy is not something you achieve by limiting yourself or by doing less, it is a set of features to be built so you can do more. We have raised money from Andreessen Horowitz and other top-tier VCs, and are excited to grow the team.
We are relentless builders, constantly pushing the boundaries of what's possible and bringing to life ideas that have never before existed. Innovation is at the core of everything we do. At Cape, we trust our team to deliver greatness and empower them to make a profound impact. As a member of our team, you will collaborate seamlessly with our diverse group of talented engineers and other team members, enjoying dynamic interactions with colleagues from across the organization.
We are looking to add our first data focused hire to build our data infrastructure from the ground up. You will be the trusted data partner across the company to (i) collaborate with engineering to capture our data needs while adhering to our privacy principles, (ii) build our data stack and implement high quality data pipelines, and (iii) create dashboards to track KPIs. The ideal candidate is a generalist who wants to split their time between building technical foundations and making sure teams can quickly run their most critical analyses. This role reports to our Head of Finance.

Requirements

• 4+ years of experience in Analytics Engineering, Data Engineering, or Business Intelligence, with ownership of production analytics systems.
• 2+ years of hands-on experience modeling analytics-ready data using dbt with SQL and/or Python.
• Expert-level SQL, including writing, optimizing, and debugging complex analytical queries.
• Proven ability to translate complex data into trusted models, metrics, and visualizations used by senior stakeholders.
• Deep experience with tools across the modern data stack
• Querying MPP analytical databases (Snowflake, Databricks, Redshift, BigQuery, etc)
• Building out BI (e.g., Omni, Tableau, Looker, Power BI, Sigma, Mode, Hex)
• Orchestrating data pipelines (e.g. Airflow, Dagster, Fivetran).
• Building transformations and semantic layers (e.g. dbt)
• Working proficiency in Python.

Nice To Haves

• Experience building and operating production data pipelines or data platforms, with strong software engineering practices (testing, CI/CD, code review).
• Experience with APIs and other integrations.
• Familiarity with AWS and self-hosted installs.
• Experience with analytics in privacy-preserving environments.

Responsibilities

• Own data pipelines: Design, build, and maintain reliable ETL/ELT pipelines, ensuring timely and accurate delivery of high-quality data across the organization.
• Create dashboards: Design and implement dashboards, while automating regular reporting workflows to reduce manual effort and increase data consistency.
• Collaborate cross-functionally: Work closely with engineering and business teams to understand use cases and proactively develop data assets that support their goals effectively and scalably.
• Improve data quality, discoverability, and metric clarity: Design and implement robust systems for schema design, data validation, documentation, and governance, while defining and standardizing core business metrics and semantic definitions to ensure consistency across teams and tools.
• Support self-serve insights: Enable teams with intuitive, trustworthy data products and tooling that allow less-technical users to explore data and develop solutions independently.
• Implement foundational tooling for our data stack (data warehouse, orchestration and transformation tools, dashboards, etc)
• Operationalize schemas needed to run high quality analytics and prepare for usage based billing models
• Partner with leaders to define and monitor key metrics across the business

Benefits

• 401(k) match
• 100% coverage of medical, dental, and vision premiums for you and your dependents
• 12 weeks paid parental leave (for all parents, no waiting period)
• Stipends for
• Family-forming needs
• Gender-affirming care

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 1-10 employees