{{Company name}} is hiring a Data Engineer to build the pipelines and platform every data decision depends on. You will make our data reliable, timely, and easy to use — so analysts, scientists, and product teams spend their time on questions, not on wrangling.

What you'll do

• Design, build, and operate batch and streaming pipelines that move data from source systems into the warehouse.
• Model warehouse data into clean, documented layers that analysts can trust and query fast.
• Set up data quality checks, freshness monitoring, and alerting — broken data should never be discovered by a stakeholder first.
• Own integrations with third-party sources and APIs, handling schema drift gracefully.
• Optimize storage and compute costs without sacrificing reliability.
• Build tooling and documentation that make self-serve data access safe.
• Partner with analysts and data scientists on the datasets their work needs next.

What we're looking for

• {{Years of experience}} years building data pipelines or data platforms in production.
• Strong SQL and solid programming skills in Python or a comparable language.
• Hands-on experience with a modern warehouse (for example a columnar cloud warehouse) and an orchestration tool.
• Practical understanding of data modeling approaches and when each fits.
• Experience debugging pipeline failures under pressure and preventing their recurrence.
• The mindset that data engineering is software engineering: version control, tests, and review apply.

Nice to have

• Experience with dbt or a similar transformation framework.
• Streaming experience (for example message-log based pipelines).
• Familiarity with infrastructure-as-code and {{Cloud provider}}.
• Exposure to data privacy and access-control requirements.

Compensation and benefits

• {{Salary range}}
• {{Benefits summary}}
• {{Location / remote policy}}

How to apply

{{Application instructions}} Tell us about the messiest data source you have tamed and what your pipeline did to keep it trustworthy.