Senior Data Engineer
The Senior Data Engineer will build scalable pipelines, ETL workflows, and data products while partnering with analytics, product, and engineering teams. The role requires 8–10+ years of experience, strong SQL and programming skills, cloud data-platform expertise, and a focus on reliability, quality, and automation.
About the job
Responsibilities
- Take loosely defined data engineering problems from framing and stakeholder alignment through solution design, implementation, and delivery.
- Partner with analytics, product, and engineering teams to deliver data solutions with business and customer impact.
- Build tools and systems that make data consistent, user-friendly, and useful.
- Ingest data from APIs, databases, SaaS applications, and event streams.
- Implement monitoring, alerting, incident response, CI/CD, automated testing, and data observability for production-grade pipelines.
- Optimize performance and cost across data workflows and storage systems.
- Leverage AI and automation to build self-service tools, intelligent pipelines, and agents that automate repetitive tasks.
Requirements and Preferred Qualifications
- 8–10+ years of industry experience in data engineering, building scalable data pipelines and data products.
- Strong proficiency in SQL and at least one programming language, such as Python, Scala, or Java.
- Experience building and maintaining robust data pipelines and ETL workflows.
- Hands-on experience with dbt for reliable, testable, and maintainable data transformations.
- Strong foundation in data modeling, schema design, and data quality best practices.
- Functional experience with cloud data platforms such as Snowflake, Redshift, BigQuery, or Databricks.
- Experience implementing CI/CD pipelines, automated testing, and data observability.
- Familiarity with monitoring, alerting, and incident response.
- Strong problem-solving, communication, collaboration, clarity, empathy, and shared-ownership skills.
Compensation and Benefits
- Targeted annual cash compensation: $155,000–$185,000 in Denver; $170,000–$200,000 in Los Angeles; and $190,000–$220,000 in San Francisco, Seattle, and New York.
- Compensation varies based on factors including experience and expertise.
- Full-time employees receive competitive base pay, benefits, and equity in the form of RSUs.
- Employees based in Denver, San Francisco, and New York work from the office approximately 2–3 days per week or more, depending on the role.
Skills
SQL, Python, Scala, Java, dbt, ETL, Data Modeling, Schema Design, Snowflake, Redshift, BigQuery, Databricks, CI/CD, Data Observability, Data Quality
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