Senior Staff Data Engineer

Job Overview

Faire’s Platform organization builds the infrastructure and systems that enable engineering, analytics, data science, product, strategy, and finance teams to operate effectively without needing to manage underlying infrastructure themselves.

Within this organization, the Data Infrastructure team owns platforms for data ingestion, storage, compute, orchestration, and governance, while the Analytics Platform team builds data warehousing capabilities, foundational data assets, and tools designed to reduce the time between data and actionable insights.

As a Senior Staff Data Engineer, you will influence these teams and the broader data organization by establishing technical direction, solving difficult architectural problems, and developing systems that remain secure, reliable, performant, scalable, and cost-efficient as Faire grows.

Key Responsibilities

• Plan and execute technical projects that allow Faire’s data systems to scale with company growth.
• Lead architecture development with emphasis on data integrity, security, performance, scalability, reliability, monitoring, and alerting.
• Help teams balance urgent operational requirements with longer-term technical priorities.
• Provide technical leadership and mentorship on complex, open-ended data engineering challenges.
• Guide decisions involving cost-efficient data compute and storage.
• Improve ETL and ELT pipelines, data ingestion systems, orchestration, and warehousing capabilities.
• Develop approaches for monitoring, alerting, and workload cost tracking.
• Establish engineering practices for foundational data assets.
• Provide guidance around data security, privacy, and governance.
• Define architecture patterns and frameworks that enable scalable analytics engineering workflows.
• Influence technical strategy across multiple Platform and Product teams.
• Work across Data Infrastructure, Analytics Platform, Product Analytics Engineering, Data Science, Strategy & Analytics, Finance, and related functions.
• Balance high-level technical leadership with hands-on engineering and development.

Required Qualifications

• Experience designing, developing, and operating large-scale data streaming and batch-processing systems.
• Experience building ETL and ELT pipelines, orchestration systems, storage platforms, compute systems, and data workflows at scale.
• Experience defining architecture patterns for reliable and scalable data platforms.
• Experience building data pipelines supporting data movement, querying, transformation, and analytics engineering workflows.
• Strong SQL skills.
• Strong Python skills.
• Experience working with data warehouses at petabyte scale.
• Strong understanding of performance, capacity, and cost tradeoffs in large-scale data processing systems.
• Ability to guide technical and product teams through infrastructure and architecture tradeoffs.
• Experience diagnosing and resolving production data-system issues at scale.
• Experience developing long-term solutions for workload performance and cost optimization.
• Experience operating within a growth-stage company with a data organization consisting of multiple teams and more than 60 people.
• Experience enabling technical teams to operate through self-service data infrastructure and tooling.
• Excellent communication, technical leadership, and influencing skills.
• Bachelor’s degree in Computer Science or Software Engineering, or equivalent industry experience.

Valuable Technical Experience

• Snowflake.
• Apache Airflow.
• Apache Spark.
• AWS.
• Python.
• Kotlin.

Core Areas of Focus

• Data infrastructure.
• Analytics platforms.
• Data architecture.
• ETL and ELT.
• Data ingestion and orchestration.
• Data warehousing.
• Data security and governance.
• Monitoring and alerting.
• Performance and cost optimization.
• Self-service data platforms.
• Technical strategy and architecture leadership.

Compensation

For candidates based in California and New York, the stated annual base salary range is $276,000–$379,500 USD.

The role is also eligible for equity and benefits. Actual base compensation is determined using factors such as transferable skills, work experience, market conditions, and primary work location.

Work Arrangement

This is a remote position in the United States and is currently open to candidates located in Arizona, California, Colorado, Connecticut, District of Columbia, Florida, Georgia, Idaho, Illinois, Indiana, Kentucky, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, Ohio, Oregon, Pennsylvania, Rhode Island, Tennessee, Texas, Utah, Virginia, Washington, or Wisconsin.

AI in the Hiring Process

Faire states that it uses Artificial Intelligence to screen and select applicants for this position.