TL;DR

Senior Data Engineer Airflow Developer: Design, develop, and deploy Apache Airflow DAGs to orchestrate Databricks jobs and build ETL workflows with an accent on performance, scalability, and reliability. Focus on refactoring reusable workflow components and collaborating with platform and DevOps teams.

Location: Seattle, WA

Salary: $111,200 - $187,740

Company

%hirify_global% is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world.

What you will do

Design, develop, and deploy Apache Airflow DAGs to orchestrate Databricks jobs.
Build and maintain ETL workflows to extract, transform, and load data.
Optimize Airflow DAGs for performance, scalability, and reliability.
Monitor Airflow and Databricks job runs, and troubleshoot execution failures.
Refactor and maintain reusable workflow components in Python.
Collaborate with platform, DevOps, and other data engineering teams.

Requirements

Hands-on experience with Apache Airflow 2.0, Databricks, PySpark, and SparkSQL.
Strong Python programming skills.
Experience designing and developing ETL processes and data pipelines in Databricks.
Solid understanding of scheduling, dependencies, and error handling in Airflow.

Culture & Benefits

Paid time off based on employee grade (vacation, company paid holidays, personal days, sick leave).
Medical, dental, and vision coverage.
Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada).
Life and disability insurance.
Employee assistance programs.