Python · SQL · NoSQL · Apache Beam · Apache Spark
ABOUT THE ROLE
Join a data product team building trusted, production-ready datasets from complex consumer information. This role combines data engineering and applied data science, with a direct connection between the products you build and customer value.
WHAT YOU'LL DO
- Investigate large, unfamiliar datasets to understand their structure, coverage, relationships, and suitability for product use.
- Design durable data models and derived attributes that turn raw information into useful data products.
- Build and operate ingestion and transformation pipelines, including validation, observability, and backfills.
- Evaluate new data sources and determine how they can improve consumer data products.
- Develop deep expertise in one or more data domains, such as identity, property, or consumer intent.
- Partner with data scientists, platform engineers, and customer-facing teams to shape ambiguous questions into scalable products.
WHAT WE'RE LOOKING FOR
- Typically 2 to 5 years of experience in data engineering, applied data science, or analytics engineering; exceptional early-career candidates are also encouraged to apply.
- Strong Python and SQL skills, with hands-on experience working with large, messy, multi-source datasets and modeling their domains.
- Experience delivering production data pipelines and customer-facing data products, beyond internal dashboards or reporting.
- Familiarity with orchestration and transformation tools such as Dagster, Airflow, or dbt, and technologies such as Snowflake, Spark, Apache Iceberg, or Trino.
- Strong compute