Airflow SME: Build Scalable Data Platforms

Synechron; Sydney; On-site; AUD 140,000 - 210,000; Full time

Job summary

Synechron is seeking a Subject Matter Expert in Apache Airflow to design, scale, and maintain robust data pipelines across cloud environments. You will collaborate with data engineers, analysts, and platform teams to ensure reliable data flow and streamlined orchestration.

The role requires hands-on engineering and architectural vision, strong Python/SQL skills, and experience with data platforms and data warehouses. Collaboration, mentoring, and DevOps practices are essential.

Qualifications

• Proven experience designing and operating data pipelines using Airflow.
• Strong Python and SQL skills for data engineering tasks.
• Experience building scalable data platforms across cloud environments.
• Hands-on with Snowflake, BigQuery or Redshift data warehouses.
• Familiarity with CI/CD and DevOps practices for data workflows.
• Ability to design robust ETL/ELT processes and monitoring.

Responsibilities

• Design, develop, and optimize data pipelines with Apache Airflow.
• Architect scalable data platforms to support analytics and ML.
• Collaborate with engineers, analysts, and platform teams for data flow.
• Implement best practices for workflow orchestration and monitoring.
• Drive automation and CI/CD integration for data workflows.
• Ensure platform reliability, security, and performance.
• Provide SME guidance on Airflow usage and DAG design.
• Mentor junior engineers and share knowledge across teams.

Skills

Apache Airflow

Python

SQL

Data pipelines

Cloud platforms

Docker

Kubernetes

Data platforms

CI/CD

DevOps

ETL/ELT

Monitoring

Communication

Tools

Snowflake

BigQuery

Redshift

Job description

Synechron is seeking a Subject Matter Expert in Apache Airflow to design, scale, and maintain robust data pipelines across cloud environments. You will collaborate with data engineers, analysts, and platform teams to ensure reliable data flow and streamlined orchestration.

The role requires hands-on engineering and architectural vision, strong Python/SQL skills, and experience with data platforms and data warehouses. Collaboration, mentoring, and DevOps practices are essential.