Key Responsibilities:
Design, develop, and manage complex Airflow DAGs for data workflows, ETL/ELT pipelines, and task automation.
Integrate Airflow with various data sources (e.g., databases, APIs, cloud storage) and targets.
Optimize and monitor pipeline performance and troubleshoot failures in a timely manner.
Collaborate with data engineers, analysts, and platform teams to support end-to-end data solutions.
Implement best practices for code quality, testing, version control, and deployment.
Maintain documentation and provide technical mentorship to junior engineers.
Required Skills:
3+ years of hands-on experience with Apache Airflow in production environments.
Strong programming skills in Python.
Solid understanding of data engineering concepts, including ETL/ELT processes, workflow orchestration, and data validation.
Experience with SQL and relational databases (e.g., PostgreSQL, MySQL).
Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and their storage and compute services.
Knowledge of containerization tools like Docker and orchestration with Kubernetes (a plus).
Compensation, Benefits and Duration
Minimum Compensation: USD 36,000
Maximum Compensation: USD 126,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.
This position is not available for independent contractors
No applications will be considered if received more than 120 days after the date of this post
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