1–3 years of professional software or data engineering experience.
Strong Python and SQL/ETL/ELT background.
Familiarity with unit tests and established codebase conventions.
Knowledge of Airflow (or willingness to learn).
Basic understanding of data pipeline concepts: ingestion, idempotency, scheduling, data quality.
Familiarity with Snowflake, Databricks, AWS, dbt, Tableau, MongoDB, PostgreSQL.
Git-based version control and PR workflows.
Strong communication; growth mindset.

$118,000–$156,000 USD

Benefits information available.

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Based on: Data Engineer II

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Implement ingestion pipelines and Airflow DAGs from a senior engineer's design, with tests and documentation.

Support data security and governance (PII masking and access controls) following established patterns.

Contribute to data delivery (reverse ETL) under guidance.

Extend fields in existing pipelines; incorporate feedback and patterns for future work.

Handle on-call pages for pipeline failures; escalate with context.

Collaborate with BI analysts, other data engineers, data scientists; participate in code and system inspections.

Mentor junior data engineers as you grow.

Define and adhere to data engineering best practices.

1–3 years of professional software or data engineering experience.
Strong Python and SQL/ETL/ELT background.
Familiarity with unit tests and established codebase conventions.
Knowledge of Airflow (or willingness to learn).
Basic understanding of data pipeline concepts: ingestion, idempotency, scheduling, data quality.
Familiarity with Snowflake, Databricks, AWS, dbt, Tableau, MongoDB, PostgreSQL.
Git-based version control and PR workflows.
Strong communication; growth mindset.