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# Staff Data Infrastructure Engineer

- **Company:** Faire
- **Location:** West Covina, CA, United States (Remote available)
- **Salary:** $246,500 - $339,000
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Airflow, Amazon Web Services, Amazon S3, Apache HTTP Server, Data Deduplication, Information Engineering, Data Governance, Data Infrastructure, Amazon DynamoDB, Python (Programming Language), MySQL, Operational Databases, Standard Sql, Scala (Programming Language), Snowflake, Apache Spark, Change Data Capture, Kotlin, Kubernetes, Apache Kafka, Terraform, Databricks
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25304_e1b414b5cea6f3465413df46f7ebaf17

## About the Role

We're looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours., * You've built and run data infrastructure that other teams depended on, at meaningful scale, and you've been the person setting direction for it, not just working on it.

 * Deep experience with change data capture and streaming ingestion from operational databases through Kafka. You know what goes wrong with ordering, duplicates, snapshots, and schema evolution because you've dealt with it.
 * Hands-on experience with lakehouse architectures on an open table format. Iceberg on S3 is what we use, so that's especially valuable. You should be comfortable talking about partitioning, compaction, catalogs, and copy-on-write versus merge-on-read.
 * Strong Spark skills, and experience running Databricks and Snowflake against shared storage.
 * Experience with data quality and observability in practice, including data contracts, SLAs, and tools like Anomalo or Monte Carlo.
 * Experience operating Airflow at scale and working with managed ingestion like Fivetran.
 * Strong SQL, and good instincts for how to model data so analysts and data scientists can actually use it.
 * Solid Python plus at least one of Kotlin, Java, Scala, or Go. Experience shipping infrastructure on AWS with Terraform.
 * A working understanding of data governance: access control, PII, retention and deletion, lineage, and audit.
 * A track record of leading cross-team data initiatives and migrations, and of mentoring senior engineers.
 * You can explain a technical tradeoff to a leadership team and to a new grad, and you can get people who disagree with each other to a decision.
 * You take ownership of things that are broken or unowned, and you're willing to be on call for the systems you build.
 * Experience in a marketplace, e-commerce, or other transaction-heavy business is a plus.

Technologies we use and teach

 * Python, Kotlin, SQL
 * Kafka, Fivetran, Airflow
 * S3, Apache Iceberg, Snowflake, Databricks, Apache Spark
 * AWS, Terraform, Kubernetes
 * CockroachDB, MySQL, Scylla and DynamoDB

## Description

* 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 the hard details like ordering, deduplication, late data, schema changes, and backfills.
 * Implement data contracts and quality checks throughout our platform
 * Put real ownership and SLAs on the datasets the business runs on, and wire quality checks into the platform with tools like Anomalo and Monte Carlo so we hear about broken data before a dashboard or a model does.
 * Run Airflow and Fivetran well, and have an opinion about what we should keep buying versus what we should build.
 * Own reliability for the platform: SLOs, on-call, incident reviews, and the follow-through so the same thing doesn't break twice.
 * Work with the senior engineers, data scientists, and analysts who depend on this platform, and lead the migration of existing pipelines onto the new one without breaking what they rely on.
 * Mentor the engineers around you. We want the team's data engineering practice to be better because you were here.