An Automation Engineer develops and implements testing strategies and toolsets with the goal of increasing process automation. Establishes appropriate measures to validate and report on software quality. Designs and implements test automation to improve system reliability and stability. Designs and supports frameworks for test infrastructure. Provides automation expertise and mentoring.
The Automation Engineer leads end-to-end project delivery, including requirements gathering, system architecture, prototyping, production deployment, and ongoing iteration.
ESSENTIAL DUTIES AND RESPONSIBILITIES
Design and build company-owned internal software, data pipelines, and integrations to replace Excel as an operational backbone Translate ambiguous business needs into clear functional and technical specifications Select appropriate tools, technologies, and architectures to deliver scalable and maintainable solutions Develop robust, efficient, and reliable systems, ensuring accuracy and correctness through validation and testing Drive execution and delivery, shipping improvements quickly and iterating based on feedback and results Replace manual workflows with production software ○ Translate informal processes into clear data models, services, and user-facing tools. ○ Build internal web apps, APIs, and automation services that users adopt. Build data pipelines and system integrations ○ Ingest data from files, forms, SaaS tools, and internal databases. ○ Implement ETL/ELT pipelines with validation, lineage, and monitoring. ○ Integrate systems via REST APIs, webhooks, queues, and scheduled jobs. Create durable data foundations ○ Design relational schemas, enforce constraints, manage migrations. ○ Build "single source of truth" datasets for analytics + operations. Operationalize ML ○ Use pre-trained models (LLMs / vision / classical ML) for classification, extraction, routing, forecasting, etc. ○ When needed: fine-tune/train on company data, evaluate properly, deploy with monitoring.
EDUCATION
Computer Science, Computer Engineering, Data Science, AI/ML
EXPERIENCE
: Proficiency in at least one backend language: e.g. Python, TypeScript/Node.js, or C#/.NET Ability to build automation/services that handle data, integrate APIs, and run reliably in production. Strong SQL and relational fundamentals (schema design basics, joins/aggregations, constraints, query debugging; Postgres/MySQL/SQL Server). Ability to build and consume REST APIs (HTTP basics, auth patterns, pagination, error handling).
