Senior Business Operations Engineer

As a Business Operations Engineer, you sit at the intersection of business, data, and technology, and you use that vantage point to scale how the organization works. Your mission is to understand our business and its processes deeply, identify where they can be made faster, simpler, and more reliable, and deliver data-driven, automated, AI-powered solutions that raise productivity, sharpen decision-making, and drive operational excellence across the company.

This is a business-first, deeply technical role. You combine a genuine understanding of how the business runs with strong engineering skills, including data engineering, programming, and enough DevOps fluency to prepare your solutions for clean, standardized handover to production.

This role is integrated in the BI team, which sits within the Finance department.

The team member shall perform the present tasks inherent to such position, including, but not limited to, the following:

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  Partner with business teams to develop a deep understanding of their processes and to identify and scope high-impact transformation opportunities through AI and automation. Define the business problem, success metrics, feasibility, risks, and ROI.

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  Map, document, and analyze the current processes, systems, and data flows across the existing tool landscape. Challenge existing processes and assumptions, identify bottlenecks, and propose new workflows and tooling that enable scalability and efficiency. 

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  Design and deliver new solutions end-to-end, from proof of concept to production. Develop automation and AI-based systems such as intelligent routing, workflow orchestration, and AI agents running in production, integrated with internal platforms via APIs and webhooks.

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  Prepare and package solutions according to the standards of the DevOps team so they can be deployed and operated in a plug-and-play manner. This does not mean acting as a DevOps engineer, but having a solid conceptual understanding of containerization (Docker), orchestration (Kubernetes), and modern deployment practices, so that what you build fits seamlessly into our operational standards.

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  Establish quality, performance, and safety monitoring for all solutions, including the LLM-powered agents running in production. Work closely with the AI team to ensure compliant usage of Agents. Create documentation, runbooks, and handovers to ensure sustainable operations.

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  Design ingestion and transformation pipelines using dbt, to support automation, analytics, and decision-making at scale.

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  Act as a catalyst for continuous improvement by challenging the status quo and driving operational excellence through innovation and simplification.

• Deep understanding of business processes, with a strong process-mapping and optimization mindset, focused on measurable efficiency gains and anticipation of edge cases and failure modes

• Strong programming skills in Python and/or Java, with strong SQL, for automation, data transformation, and system integration

• Proven experience building and maintaining ETL/ELT pipelines using dbt or similar frameworks

• Hands-on experience executing automations

• Practical experience with LLMs and AI agents, including building and running agentic workflows in production, and a habit of actively keeping up to date with the fast-evolving developments in the field

• Solid conceptual DevOps knowledge, including containerization (Docker), orchestration (Kubernetes), and deployment practices, sufficient to prepare solutions to the standards of a DevOps team for smooth, standardized deployment

• Familiarity with integrating APIs and webhooks to automate cross-system workflows

• Experience working with cloud platforms such as AWS, GCP, or Azure

• Excellent collaboration, stakeholder communication, and ownership across technical and business teams, and participates in code/design reviews

• A proactive and self-driven mindset, with a passion for solving complex problems through simple, scalable solutions, understanding cost vs. performance tradeoffs