Data Engineer I
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Job Description
Data Engineer I developing analytics-ready datasets and metrics for Capital Rx. Collaborates across teams to optimize and enhance data reporting and quality.
Responsibilities:
- Partner closely with operational and analytics teams to translate business needs into analytics-ready data models, curated data marts, and reusable datasets.
- Build and maintain dbt projects (staging → intermediate → marts), including model layering, macros, exposures, packages, and source freshness to accelerate delivery and improve reliability.
- Design and evolve dimensional models (facts/dimensions, grain, SCD patterns) and analytics patterns aligned with key business domains.
- Own metrics definitions end-to-end: establish KPI logic, naming standards, calculation rules, and governance; maintain a metrics/semantic layer so stakeholders use consistent definitions across tools and teams.
- Implement robust data quality practices (dbt tests, constraints, anomaly checks/monitoring) to ensure reliable downstream reporting and decision-making.
- Produce clear documentation and enablement assets (dbt docs, lineage, data dictionaries, metric definitions, onboarding guides) to support self-service analytics.
- Optimize warehouse performance and cost in Snowflake through SQL tuning, incremental models, appropriate materializations, and efficient data design.
- Use disciplined software engineering practices (Git-based workflows, peer review, CI checks, versioning, environment promotion) to deploy changes safely and repeatably.
- Proactively identify and resolve data-related issues, ensuring system reliability and data integrity.
- Provide ongoing support for critical analytics data products and participate in an on-call rotation as needed.
- Responsible for adherence to the Capital Rx Code of Conduct including reporting of noncompliance.
Requirements:
- Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent practical experience).
- Strong SQL skills and experience building analytics datasets in a modern cloud data warehouse (Snowflake preferred).
- Hands-on experience with dbt core (model development, tests, documentation, macros, deployments).
- Solid foundation in data modeling (dimensional/Kimball concepts, facts/dimensions, grain, slowly changing dimensions).
- Experience defining and managing metrics: translating business logic into consistent KPI definitions, documenting edge cases, and maintaining metric governance over time.
- 1+ years of experience delivering production-grade analytics models/marts or BI-ready datasets (internships/co-ops may be considered depending on leveling).
- Ability to collaborate effectively with both technical and non-technical stakeholders; strong communication and documentation skills.
- A self-motivated, detail-oriented individual with the ability to tackle and solve intricate technical challenges and deliver high-quality work.
Benefits:
- Health insurance
- 401(k) matching
- Flexible work hours
- Paid time off
- Remote work options
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