Senior Data Engineer

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CI job seekers.

We prioritize the health and wellbeing of our employees through our comprehensive benefit package, including generous paid time off to rest and recharge, holistic mental health support, and benefits covering employees up to 100%.

At Circle

CI, employees have ample opportunity to learn new skills, including project-based learning and presentations from our colleagues. Your continued professional development is important to us because it’s important to you.

What does it mean to work at Circle

CI? For us, flexibility is key.

We’re looking for a Staff Data Engineer to shape the future of our data platform. You’ll architect scalable systems, set technical direction, and build the frameworks that enable our data organization to operate s is a high‑leverage role where your work multiplies the effectiveness of the entire team.

• Own the technical roadmap for our data platform, making architectural decisions that balance scalability, cost, and maintainability
• Evaluate and champion new technologies and tools, leading adoption across the organization
• Design systems for terabyte‑scale data processing with a focus on performance and cost optimization
• Establish data engineering standards, patterns, and best practices that elevate team quality
• Model infrastructure costs and drive efficiency initiatives across Snowflake and cloud platforms

• Design and build scalable infrastructure for AI/ML workloads, including model training pipelines, feature engineering systems, and AI agent platforms
• Build reusable frameworks and internal platforms that abstract complexity for other engineers
• Design complex data models for critical business domains, balancing normalization, performance, and usability
• Architect real‑time/streaming data infrastructure for low‑latency use cases
• Engineer solutions for large‑dataset performance challenges (Snowflake clustering, micro‑partitioning, query optimization)
• Create sophisticated data‑contract validators and schema evolution frameworks
• Develop profiling and drift detection systems that ensure data quality at scale

• Conduct design reviews and provide architectural guidance for major initiatives
• Lead incident response for critical data systems and drive blameless post‑mortems
• Define SLAs and reliability standards for data products
• Mentor and upskill data engineers through pairing, code reviews, and technical discussions
• Lead cross‑functional projects with analytics, data science, and product teams

• Build data observability platforms with intelligent alerting and monitoring
• Perform capacity planning and scalability analysis for the entire data stack
• Benchmark performance across infrastructure to identify optimization opportunities
• Design self‑service tools that enable analytics engineers and analysts to work independently

• Deep expertise with modern data warehouses (Snowflake strongly preferred) including advanced optimization techniques
• Strong foundations in distributed systems, data structures, and algorithms
• Production experience building high‑volume data pipelines and ETL/ELT systems
• Proficiency in Python/SQL and orchestration tools (Airflow, dbt, or similar)
• Experience with cloud platforms (AWS/GCP) and infrastructure‑as‑code

• Track record of making architectural decisions with long‑term impact
• Ability to evaluate tradeoffs between competing approaches
• Experience balancing technical excellence with business pragmatism
• Proven ability to drive technical strategy across an organization

• History of mentoring engineers and raising team capabilities
• Excellent written and verbal communication for technical and non‑technical audiences
• Ability to build consensus and influence without direct authority
• Experience leading projects across multiple teams

• Experience with streaming systems (Kafka, Flink, etc.)
• Data mesh or domain‑oriented architecture implementation
• Open source contributions or technical writing
• Background in analytics engineering…