Data Engineer

Role overview Build and support cloud data pipelines that bring information from varied sources into reliable, analytics-ready datasets. The work spans data ingestion, transformation, quality, and automation, with close collaboration across engineering, analytics, and business teams.

Responsibilities - Develop and maintain pipelines and data models using SQL, Python, and cloud data platforms. - Ingest and transform data from APIs, databases, cloud storage, marketing tools, and other external sources. - Create reusable transformation workflows with dbt or a similar framework. - Add validation, monitoring, and troubleshooting practices to improve data reliability. - Automate manual work and improve pipeline performance, scale, and maintainability. - Use AI-assisted tools for development and documentation, checking their output for accuracy and security.

Requirements - At least two years of experience in data engineering, analytics engineering, or a related technical role. - Strong SQL skills and experience supporting production data pipelines. - Hands-on experience with Snowflake or BigQuery, plus working knowledge of Python. - Familiarity with dbt or similar transformation tools and AWS or Google Cloud. - Understanding of data modeling, ETL/ELT, Git, and data quality practices. - Strong troubleshooting and communication skills; a related degree or equivalent practical experience.

Nice to have Experience with Fivetran, Supermetrics, a BI platform, CI/CD, orchestration, automated testing, data governance, or marketing, CRM, advertising, or healthcare data integrations.

Benefits and work setup Hybrid and remote schedules are available. Benefits include health, dental, and vision coverage; disability and life insurance; FSA/HSA options; a 401(k) with company match; flexible paid time off; paid parental leave; and employee assistance and referral programs. Applicants must live in the United States and be authorized to work there.