Senior Data Engineer

CircleCI

4h•$155,000 - $193,000

About The Position

We're looking for a Sr. 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 at scale. This is a high-leverage role where your work multiplies the effectiveness of the entire team.

Requirements

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

Nice To Haves

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

Responsibilities

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