Data Engineer

Cape•New York, NY

About The Position

As a Data Engineer at Cape, your mission is to build the analytics and reporting infrastructure that lets us understand our product and business without compromising the privacy guarantees we make to our customers. Privacy isn't a constraint layered on top of our data systems; it's a design requirement baked into them from the start. You'll chart the course for Cape’s data infrastructure and your work will give the business first-class visibility into growth, operations, and product health built the right way from day one.

Requirements

4+ years of professional data engineering or software engineering experience, with meaningful time building data pipelines and warehouses.
Strong SQL and data modeling skills, with experience designing schemas for analytics workloads.
Fluency in Python, Go, or another backend language.
Hands-on experience with a cloud data warehouse such as Snowflake, BigQuery, MongoDB or Redshift.
Familiarity with ETL/ELT frameworks and workflow orchestration tools.
A solid understanding of privacy-preserving data practices including access control, data minimization, and identifier management.
Strong written and verbal communication skills, with the ability to work effectively across engineering, product, and business stakeholders.

Nice To Haves

Experience in a regulated or privacy-sensitive industry (telecom, healthcare, fintech).
Background in differential privacy, k-anonymity, or other formal privacy models.

Responsibilities

Own the Infrastructure: Design and build Cape's data platform from the ground up, spanning the warehouse, query layer, and pipeline orchestration, built with privacy as a first-class requirement from day one.
Privacy-First by Default: Work closely with engineering to establish privacy-preserving patterns and practices that the rest of the company builds on.
Enable the Business: Give product, operations, and leadership the self-serve analytics they need such as dashboards, metrics, and reports that answer real questions.
Set the Standard: Establish the data engineering practices Cape will build on such as pipeline conventions, testing, documentation, and a culture of treating data infrastructure with the same rigor we apply to our telecom stack.