Senior Data Engineer

SingleOps

full-time

Posted on: 9/5/2025

Origin: • 🇺🇸 United States

✨ AI Apply

Senior

AirflowAzureCloudPythonScalaSQLTerraform

About the role

Build and maintain scalable, modular data pipelines using tools like dbt and Azure Data Factory
Design batch and streaming data workflows that support near-real-time reporting and operational intelligence
Deliver high-quality, trusted datasets to enable analytics, dashboards, embedded apps, and AI use cases
Influence and guide the evolution of our data platform tooling and architectural decisions
Contribute to structured architectural patterns such as Medallion for layered, reusable data models
Drive data quality through testing, observability, and proactive alerting (e.g. dbt test, data contacts)
Partner across engineering, product, and analytics teams to improve velocity, reusability, and access to data with documentation, lineage, and governance
Collaborate on architecture and tooling that powers insight and action for customer-facing and internal use cases

5+ years of experience in data engineering or analytics engineering roles
Deep mastery of SQL and extensive, hands-on experience with Snowflake
Strong experience with dbt or similar data transformation frameworks
Proficient in Python, Scala, or similar languages used in data pipeline logic/automation
Experience with orchestration tools like Azure Data Factory, Airflow, or similar
Comfortable working in a modern, git-based development environment with CI/CD
Experience with cloud-native data streaming technologies such as Azure Event Grid
Exposure and understanding of Data Architectural patterns such as Medallion
Experience using Infrastructure as Code tooling; Terraform is a bonus
Bonus: Experience with Snowflake features such as Cortex, Data Shares, Snowpark
Bonus: Experience with data visualization tools such as Redash and Gooddata
Bonus: Experience with semantic modeling or enabling data for AI applications
Experience productionizing batch and streaming pipelines that scale
Experience contributing to tooling decisions or platform evolution in a growing data team
Experience supporting external data products, analytics features, or ML/AI-powered applications
Ability to balance speed and governance across data lifecycle and tooling
Must have proper work authorization to work for any employer in the United States; company does not sponsor work authorization