• Develop end-to-end automation scripts and workflows using Power Automate, Azure Logic Apps, and Azure Functions.
• Build and manage data-driven automations, ensuring seamless data flow between databases (SQL, Oracle, PostgreSQL) and enterprise applications.
• Collaborate with Data Engineers and Scientists to move manual data handling and model execution into automated, production-ready pipelines.
• Monitor existing automated workflows, troubleshooting failures, and performing root-cause analysis to ensure high uptime.
• CI/CD Support: Use GitHub Actions or Azure DevOps to version control automation code and deploy updates safely across environments.
• Perform rigorous testing of automated logic to ensure accuracy, handling "edge cases" and exceptions to prevent process breaks.
• Create clear process maps and technical documentation for every automated workflow to ensure transparency and auditability.
• Integrate third-party tools and internal systems via REST APIs to trigger actions and sync data automatically.
• Document processes and ensure compliance with data governance, privacy, and auditability requirements.
• Stay up to date on emerging Automation and cloud technologies to improve operational efficiency.

Prefered Skills

Proven experience as an Automation Engineer, RPA Developer, or Data Engineer with a focus on workflow orchestration.
• Practical experience with Microsoft Fabric, Azure Data Factory, Synapse and Data Lake.
• Proficiency in Python for scripting and data manipulation. Knowledge of PowerShell or Bash is beneficial.
• Strong SQL (PostgreSQL, Oracle, MSSQL) skills for querying and managing data within automated steps.
• Experience using ETL Tools for automated data movement.
• Understanding of Docker containers and basic CI/CD pipeline structures.
• Strong ability to break down a manual business process into a logical, step-by-step automated flow.
• Ability to work effectively with cross-functional teams to understand requirements and deliver functional solutions.
• A proactive learner who can quickly pick up new cloud services and automation frameworks.
• Financial services industry knowledge is preferred.
• Strong organizational skills, detail-oriented, and able to work under pressure with tight deadlines.
• Familiarity with data governance and responsible AI frameworks.
• Strong collaboration skills to work with Data Scientists, Engineers, and Business Stakeholders.
• Excellent problem-solving and troubleshooting skills in production environments.
• Growth mindset, with ability to learn and adapt quickly in a fast-paced setting.