Lead Data Engineer

About this role

We're looking for a Lead Data Engineer to own the reliability and operational excellence of our data platform. You'll work hands-on across
Snowflake, Airflow, AWS, Python, and SQL
, building and operating systems that support analytics, machine learning, and business decisions.


This is a
technical leadership role, but it is also deeply hands-on
. You'll write code, debug pipelines, tune performance, and operate production systems. You’ll also set standards, lead incidents, drive cost optimization, and remove technical blockers across teams. The expectation is simple: you do the work, and you set up the bar for how the work gets done.


Responsibilities
What You’ll Do

• Build, maintain , and operate data pipelines and curated data products across Snowflake, Airflow (MWAA), AWS, Python, and SQL.
• Optimize Snowflake architecture at scale. Design warehouse strategies, implement clustering and materialized views, enforce resource monitors, control costs, and tune performance across large datasets.
• Implement observability and data quality controls. Build monitoring for freshness, volume, schema, distribution, and lineage. Define data quality SLOs and ensure teams can see issues before users do.
• Support and operate production data systems. Troubleshoot failures, respond to alerts, debug pipeline issues, and improve system behavior based on real incidents.
• Own SLAs, uptime, and service commitments for data platforms and critical services. Monitor performance, track reliability metrics, and make sure availability and freshness targets are met.
• Lead major incident responses and postmortems. Coordinate resolution during critical outages, drive root cause analysis, and implement corrective actions that prevent recurrence.
• Architect data platforms across dev, test, and production. Design for disaster recovery, upgrades without downtime, automation that recovers from failure, and availability that supports business continuity.
• Define and en...