Data Scientist
Cape
full-time
Posted on:
Location Type: Hybrid
Location: New York City • New York • United States
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About the role
- 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.
- Priority projects:
- 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
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.
- Preferred
- 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.
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
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
ETLELTSQLPythondbtdata modelingdata validationdata governancedata visualizationanalytics
Soft Skills
collaborationcommunicationproblem-solvingproactive developmentdata discoverabilitymetric clarityself-service insightsstakeholder engagementorganizational skillsattention to detail