Data Engineer San Francisco, CA
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Entrepreneur & Recruitment Director Building High-Performing Teams Cutting Costs & Securing Top Tech Talent
Data Engineer Cloud-Native High-Impact Products Remote 75,000 95,000 + Benefits
One of the Most In-Demand Data Engineering Roles on the Market Right Now
Were partnered with a fast-scaling, product-led tech company thats making serious waves in their industry, and data is at the core of it all. Theyre building smarter, scalable platforms that help customers in real-time, and now theyre looking for a Data Engineer who can help architect the systems that make that possible.
This is not just another data team hire, youll be pivotal in designing, building, and scaling cloud-based data infrastructure that powers critical business intelligence, product insights, and machine learning.
What Youll Be Working On:
Building robust, scalable data pipelines (batch + real-time) using Spark, Kafka, Airflow, dbt
Designing warehouse architectures on Snowflake, BigQuery, or Redshift
Developing ETL/ELT solutions that transform billions of records with performance and governance in mind
Integrating APIs and external data sources into a unified data platform
Partnering cross-functionally with data scientists, engineers, and product teams to deliver value-driven insights
Implementing data observability, lineage, and quality frameworks to support growth at scale- The Tech Youll Use:
Warehousing: Snowflake, BigQuery, Redshift
Streaming: Kafka, Kinesis
Languages: Python, SQL, Bash
What We're Looking For:
3+ years of experience as a Data Engineer working with modern data stacks
Proven experience building and maintaining pipelines in production
Experience with event-driven architecture and cloud-native environments
A keen understanding of data privacy, security, and governance best practices
Bonus points for experience with tools like Looker, Power BI, or Tableau
High-impact role: Your work directly supports real-time decision-making for thousands of usersModern stack: No legacy systems, no duct tape build the right way from the start
Remote-first: Work from anywhere, with flexible hours
Backed for growth: Youll have a budget for tools, training, and conferences
Culture-led: Empowered teams, low ego, lots of collaboration
Screening Questions:
Describe a complex pipeline youve built what made it challenging?
How have you used streaming technologies like Kafka or Kinesis?
Whats your go-to stack for building a modern data platform, and why?
Have you worked with dbt or Airflow in a production setting?
Whats your approach to handling schema evolution and bad data?
Seniority level
Seniority level
Mid-Senior level
Employment type
Employment type
Full-time
Job function
Job function
Product Management and Information Technology