Senior Apache Airflow Platform Engineer

Architect, deploy, and manage production-grade Apache Airflow/Astronomer platforms on Kubernetes.

Manage platform upgrades, high availability, scalability, capacity planning, security, and performance optimization.

Automate infrastructure provisioning and platform lifecycle using Terraform, Helm, Git Ops, and CI/CD pipelines.

Develop reusable DAG templates, custom operators, shared libraries, testing frameworks, and self-service tools.

Implement monitoring, logging, alerting, SLA tracking, incident management, and disaster recovery.

Optimize workflow scheduling, task concurrency, retries, backfills, and resource utilization.

Implement access controls, secrets management, audit logging, and security best practices.

Collaborate with data engineering and platform teams, mentor engineers, and define platform standards and roadmaps.

6+ years of experience in data engineering, platform engineering, or infrastructure systems.

3+ years of hands-on Apache Airflow production experience at scale.

Strong expertise in Astronomer, Airflow DAGs, operators, sensors, dynamic task mapping, scheduling, and workflow optimization.

Strong Kubernetes, Helm, Terraform, Git Ops (Argo CD/Flux), and CI/CD experience.

Proficiency in Python and Bash scripting.

Experience with Prometheus, Grafana, centralized logging, monitoring, and SRE practices.

Knowledge of AWS, Azure, or GCP, including IAM, networking, and cloud storage.

Experience with security, RBAC, SSO/OIDC, secrets management, incident response, and high-availability architecture.

Experience with Snowflake, Big Query, Redshift, Databricks, Spark, or dbt.

Familiarity with Open Lineage, Marquez, data quality frameworks, and data contracts.

Experience with multi-region disaster recovery, platform migrations, and cost optimization.

Contributions to Apache Airflow or development of internal developer platforms.