Staff Data Infrastructure Engineer

About this role

Our Engineering organization owns the software that makes our marketplace work. The Data Platform group supports everyone at Faire who depends on data: Product Engineering, Data Science, Machine Learning, Analytics, Strategy, Finance, and Product. Our job is to make sure the data is there, it's right, and people can find it and query it without having to think about the plumbing underneath.

We are hiring a Staff Engineer to own that plumbing. Concretely, this means the path data takes out of our production databases (CockroachDB and MySQL) and into a place where analysts and data scientists can query it. Today that involves Fivetran, Kafka, Spark, and Airflow landing data in Snowflake and Databricks. We want someone who can design the next version of it, build the hard parts personally, and bring the rest of the company along.

What you'll do

• Set the technical direction for how data moves from production systems into our analytical stores, and own the roadmap to get there over the next couple of years.
• Build the CDC and streaming ingestion layer: CockroachDB changefeeds and MySQL binlogs into Kafka, then into Iceberg tables on S3. You'll be responsible for ordering, deduplication, late data, schema changes, and backfills.
• Implement data contracts and quality checks throughout our platform.
• Put real ownership and SLAs on datasets, wiring quality checks into the platform with tools like Anomalo and Monte Carlo.
• Run Airflow and Fivetran well, and evaluate buy versus build decisions.
• Own reliability for the platform: SLOs, on-call, incident reviews, and follow-through.
• Work with senior engineers, data scientists, and analysts to lead pipeline migrations.
• Mentor engineers across the team.

Qualifications

• Deep experience with change data capture and streaming ingestion from operational databases through Kafka.
• Hands-on experience with lakehouse architectures on an open table format (Iceberg on S3).
• Strong Spark skills, and experience running Databricks and Snowflake against shared storage.
• Experience with data quality and observability in practice (data contracts, SLAs, tools like Anomalo or Monte Carlo).
• Experience operating Airflow at scale and working with managed ingestion like Fivetran.
• Strong SQL and instincts for data modeling for analytics and data science.
• Solid Python plus at least one of Kotlin, Java, Scala, or Go.
• Experience shipping infrastructure on AWS with Terraform.
• Working understanding of data governance: access control, PII, retention, deletion, lineage, and audit.
• Track record of leading cross-team data initiatives and migrations, and mentoring senior engineers.
• Strong technical communication and decision-making skills across leadership and engineering.
• Willingness to take ownership and participate in on-call rotation.
• Experience in a marketplace, e-commerce, or other transaction-heavy business is a plus.