Staff Data Infra Engineer: Scale Pipelines & Reliability

D8 LooP; New York (NY); On-site; USD 120,000 - 170,000; Full time

Job summary

Faire is a technology wholesale platform connecting independent retailers worldwide. We are seeking a data-focused engineer to architect and manage scalable data pipelines, ensure data quality, and enable analysts with reliable, streaming ingestion across systems.

You will own reliability metrics and collaborate with teams to reduce data latency and improve schema evolution handling. The role emphasizes building CDC/high-volume streaming workflows using modern data tooling and cloud platforms,

Qualifications

• Experience operating Airflow at scale and with managed ingestion like Fivetran.
• Experience with data quality and observability, including data contracts and SLAs.
• Strong Python plus at least one of Kotlin, Java, Scala, or Go.
• Strong SQL and data modeling for analysts and data scientists.
• Strong Spark skills; Databricks and Snowflake against shared storage.
• Deep experience with CDC and streaming ingestion from operational databases via Kafka.
• Knowledge of ordering, deduplication, late data, schema changes, and backfills.
• You understand issues with ordering, duplicates, snapshots, and schema evolution.
• Build CDC/streaming ingestion using CockroachDB, MySQL, Kafka, Iceberg on S3.
• Own reliability: SLOs, on-call, incident reviews, and follow-through.

Skills

Airflow orchestration

Data quality observability

Python

SQL

Spark

Streaming / CDC

Idempotency & backfills

Ordering, duplicates & schema changes

SLOs & on-call

Incremental loads

Tools

Fivetran

Anomalo

Monte Carlo

Databricks

Snowflake

Kafka

CockroachDB

MySQL

Iceberg

S3

Terraform

AWS

Airflow

Job description

Faire is a technology wholesale platform connecting independent retailers worldwide. We are seeking a data-focused engineer to architect and manage scalable data pipelines, ensure data quality, and enable analysts with reliable, streaming ingestion across systems.

You will own reliability metrics and collaborate with teams to reduce data latency and improve schema evolution handling. The role emphasizes building CDC/high-volume streaming workflows using modern data tooling and cloud platforms,