Data Operations Engineer

Responsibilities

• Own the full lifecycle of partner data as it moves through our systems
• Balance partner trust, engineering velocity, and long-term data platform health while enabling intelligent, contract-driven data exchange
• Guide data architecture decisions that incorporate AI-augmented capabilities into workflows for partner integrations
• Partner with Product, Engineering, and partner teams to develop flexible data roadmaps
• Drive pipeline improvements that scale across diverse partner data formats
• Maintain adaptable data contracts and schema strategies
• Identify and drive cross-platform improvements that enhance partner and developer experiences
• Collaborate across Engineering, Product, and partner teams to deliver AI‑first, integration‑ready data solutions
• Own ambiguous data challenges and drive them to resolution
• Mentor engineers and analytics contributors through coaching and feedback
• Ensure new partnerships are delivered with care, reliability, and ingenuity

• Strong experience designing and operating data pipelines with defined latency, freshness, and accuracy SLAs
• Expert SQL skills and proven ability to work with large, complex datasets across diverse partner schemas
• Hands‑on experience with modern data tooling such as Snowflake, dbt, Airflow, and schema registries
• Practical, in‑the‑workflow use of agentic tooling to accelerate schema mapping, anomaly detection, data profiling, and pipeline debugging
• Track record of building monitoring, alerting, runbooks, and reconciliation processes for systems with external commitments
• Ability to ramp quickly on new partner ecosystems, data formats, and domains
• Proven success leading work in ambiguous, fast‑moving environments
• Excellent collaboration, communication, and cross‑team influence