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Data Engineer
Cleerly
- New York, New York, United States
- New York, New York, United States
À propos
5+ years of experience in a data engineering or analytics engineering role
Strong proficiency in SQL and hands‑on experience with Snowflake, including warehouse management, query optimization, and data modeling patterns
Experience with dbt (Core or Cloud) for building and maintaining modular, tested transformation pipelines
Demonstrated ability to work closely with business stakeholders to define and implement metrics and data definitions — not just build pipelines
Solid understanding of dimensional modeling, data vault, or other warehouse modeling approaches
Experience with workflow orchestration tools such as Airflow, Dagster, or Prefect - you'll be creating and improving the DAGs that drive our Snowflake pipelines end to end
Hands‑on experience with AWS data services - S3, MWAA, and CloudWatch - supporting production data pipelines in a cloud‑native environment
Ability to work through ambiguity and exercise good judgment when translating loosely defined business requirements into structured data models
Bachelor's degree in Computer Science, Engineering, Math, or a related field, or equivalent practical experience
What the job involves
The BI & Data team at Cleerly provides in-depth analysis that puts data and insights at the heart of decision making. We are a team of engineers, product managers, and analysts located across the U.S. with a passion for data architecture, visualization, and analysis
Own the design, development, and maintenance of data models within Snowflake that serve as the foundation for business metrics, reporting, and analytics across the organization
Partner closely with business stakeholders to translate operational definitions and KPIs into reliable, well‑documented data structures
Build and maintain dbt models that power our core metrics layer, ensuring accuracy, consistency, and reusability across teams
Manage and evolve our Snowflake data warehouse, including schema design, performance optimization, and data organization best practices
Collaborate with analytics and BI teams to ensure the data layer supports self‑serve reporting and business review cadences
Contribute to data modeling standards and best practices that allow the team to scale with confidence
Participate in strategic discussions around data architecture and help evaluate trade‑offs across build vs. buy decisions
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Compétences linguistiques
- English
Avis aux utilisateurs
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