Senior Airflow & Cloud Automation Engineer

Deutsche Bank; Birmingham; On-site; GBP 65,000 - 95,000; Full time

Job summary

Deutsche Bank in the United Kingdom is seeking a software engineer focused on workload automation to ensure availability, latency, and efficiency of centralized platforms such as Control-M, Automic, Airflow and Google Cloud Composer.

You will develop in Python, integrate REST APIs, and design automation using Ansible and Terraform, contributing to monitoring, change management and capacity planning across batch scheduling systems.

Qualifications

• Experience with Python development and API orchestration for workload automation platforms.
• Proficiency in Airflow and Google Cloud Platform services including Cloud Composer, BigQuery, Dataflow, Dataproc.
• Hands-on experience with Control-M or Automic is a plus and REST-based API orchestration.

Responsibilities

• Develop and implement automation for Control-M, Automic, Airflow and Google Cloud Composer.
• Integrate with REST APIs and orchestration layers to drive workload automation.
• Design improvements and replacements for existing processes, especially replacing Control-M/Automic with Airflow or Cloud Composer.
• Install, configure, monitor Airflow clusters, tune DAGs and data pipelines.
• Contribute to capacity planning, change management and proactive monitoring across centralized platforms.

Skills

Python

API integration

Orchestration

REST API

Airflow

Google Cloud Platform

Control-M

Automic

Ansible YAML

SDLC / Agile

DAG development

Performance tuning

Data engineering basics

Tools

Terraform

Cloud Composer

BigQuery

Dataflow

Cloud Functions

Dataproc

Postgres

Ansible

Job description

Deutsche Bank in the United Kingdom is seeking a software engineer focused on workload automation to ensure availability, latency, and efficiency of centralized platforms such as Control-M, Automic, Airflow and Google Cloud Composer.

You will develop in Python, integrate REST APIs, and design automation using Ansible and Terraform, contributing to monitoring, change management and capacity planning across batch scheduling systems.