Coordinate with analytics engineers, data engineers, product teams, and business stakeholders during production issues. Extensive hands-on experience building and maintaining production dbt projects .
Numbers & Facts
Location
Remote, U.S., NY (Remote)
Salary
$45–$50
Description
Ownership
Build, enhance, and maintain production dbt models.
Extend existing dimensional models using established patterns.
Develop transformations across structured and semi-structured datasets.
Work across Silver and Gold layers within a medallion architecture.
Write and optimize complex SQL against large datasets.
Monitor and troubleshoot production data pipelines.
Investigate data quality issues and implement fixes.
Diagnose unfamiliar datasets, code, and upstream dependencies independently.
Participate in code reviews, testing, deployment, and documentation.
Coordinate with analytics engineers, data engineers, product teams, and business stakeholders during production issues.
Technical Environment
Core:
SQL
dbt
Databricks
AWS
GitHub
Additional Environment:
Unity Catalog
PySpark
Distributed data processing
GitHub Actions / CI/CD
Dimensional modeling
Medallion architecture
Structured and semi-structured data
Production data pipelines
AI-assisted development, including GitHub Copilot
Must-Haves:
5+ years in Analytics Engineering, Data Engineering, or engineering-heavy Data Analytics.
Expert SQL with complex query development, optimization, and data modeling.
Extensive hands-on experience building and maintaining production dbt projects.
Experience with cloud-based data platforms, preferably AWS.
Modern data platform experience such as Databricks, Unity Catalog, Snowflake, or similar.
Experience supporting production data pipelines.
Strong troubleshooting and root-cause analysis skills.
Ability to investigate unfamiliar systems independently.
Strong communication across technical teams.
Evidence of writing maintainable, production-quality code.