Staff Data Engineer

RevolutionParts is a pioneering force in automotive eCommerce, empowering automotive brands to maximize online sales through streamlined, user-friendly solutions. We’re looking for passionate individuals to join our team of Revolutionaries and help transform the eCommerce space for automotive parts and accessories.

About the role

This data engineering role goes beyond managing a Jira board—it hands you a whiteboard and asks what should be on it. RevolutionParts powers parts and accessories commerce for thousands of automotive dealers and OEMs across North America. The data behind it (catalog, pricing, inventory) flows through a high-volume ingestion system built for our past scale, not our future. We need someone who can maintain reliability today while defining and executing a migration to a next-generation architecture. The target architecture doesn’t exist yet, and the technical bar for this domain will be set by whoever takes this role.

Responsibilities

• Strategic Leadership & Architectural Ownership
  • Serve as the technical authority for data ingestion at RevolutionParts, leading through expertise.
  • Own the 2-3 year architectural vision for data ingestion, including destination, migration sequence, tradeoffs, and retirement criteria for the current system.
  • Set engineering standards for schema design, data contracts, query optimization, and observability—establishing the organization’s baseline.
  • Shape technical strategy across Product, BI, Platform Engineering, and Executive Leadership, driving alignment and owning outcomes for complex multi-quarter initiatives.
  • Take ownership of the highest-severity, most ambiguous data problems that cross team boundaries and resist resolution.
• Execution & Operational Excellence
  • Hold ultimate accountability for the architecture and production performance of catalog, pricing, and inventory ingestion systems.
  • Define the reliability bar for data, building monitoring, alerting, and validation frameworks to turn data quality into a contractual commitment with SLAs.
  • Make final, binding technical debt decisions for the ingestion domain, balancing stability and long-term health with clear documentation.
  • Mentor Senior Engineers on distributed systems, high-volume database performance, and data modeling at scale to elevate the team’s technical ceiling.

Requirements

• 10+ years in data or software engineering, with at least 3 at Staff level or equivalent, owning architectural decisions for high-volume production systems.
• Expertise in Python and Spark/PySpark at petabyte scale, including tuning Spark from first principles (partition strategy, join optimization, dynamic allocation, skew diagnosis).
• Designed and operated distributed job execution systems with dynamic compute provisioning, variable workload profiles, job isolation, and resource contention at scale.
• Deep experience with message queue architectures in production, including fan-out patterns, poison pill handling, dead letter queues, and consumer lag at scale.
• Built observability into systems from the ground up—monitoring, alerting, lineage, and pipeline health—not just bolted-on dashboards.
• Built pipeline orchestration infrastructure with strong opinions on operability, having inherited systems that lacked it.
• Led a migration from legacy batch infrastructure (custom schedulers, daemon-based systems, cron pipelines) to modern architecture without downtime.
• Deep AWS production experience: EKS, EC2 fleet management, SQS, RDS, operated at scale.
• Kubernetes in production, including workload behavior, compute right-sizing for variable job profiles, and failure modes under load.
• Streaming in production: Kafka, Flink, Kinesis, or Redpanda, with experience making batch-vs-streaming decisions.
• Cloud data warehouse architecture: Snowflake, BigQuery, or Databricks, including clustering, partitioning, cost management, and mixed workloads.
• Daily use of AI coding tools to ship production work, with examples of improving outcomes in prior roles.
• Ability to write trusted architecture docs and brief executives on technical decisions.
• BS or MS in Computer Science, Engineering, or equivalent.
• AI Fluency & Modern Tooling
  • Use AI tools responsibly to accelerate research, analysis, documentation, and problem-solving.
  • Exercise strong judgment around data privacy, accuracy, and ethical use.
  • Continuously learn and adapt as AI capabilities evolve.

Benefits

RevolutionParts provides all full-time employees with a comprehensive employment package, including:

• Competitive compensation
• Career development opportunities
• 401K match
• Parental leave
• Additional valuable perks

Pay

The base pay range for this role is $170,000 – $185,000 per year.