Business Intelligence & Automation Analyst

Adobe•San Jose, CA

14d

About The Position

Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours! Join the Adobe Unified Platform Business Operations & Strategy team at Adobe to build and evolve the technical backbone of our operational ecosystem. This role is critical to ensuring our systems, automations, and data infrastructure scale efficiently across a large platform organization. You’ll design, maintain, and optimize the pipelines, tools, and workflows that power planning, reporting, and execution — all while exploring new ways to integrate AI and LLMs to drive automation and insight at scale. This position is ideal for someone who thrives at the intersection of engineering and operations — someone who can write code, understand systems, and translate operational needs into robust technical solutions.

Requirements

Technical Expertise Strong proficiency in Python (automation, scripting, APIs, data processing).
Experience with ETL pipelines, SQL, and database management (e.g., MySQL, PostgreSQL).
Familiarity with CI/CD tools such as Jenkins, GitHub Actions, or similar.
Comfort working in cloud or containerized environments (AWS, Azure, GCP, Docker a plus).
Experience with APIs, webhooks, and system integrations.
AI & Innovation Demonstrated curiosity and hands-on experience using LLMs or AI tools to increase efficiency or generate insights.
Ability to translate operational or analytical problems into opportunities for AI-assisted automation.
Operational Competence 3–5 years of experience in a technical operations, data engineering, or business systems role within a SaaS or platform-focused organization.
Familiarity with the rhythms of strategizing, documenting, and implementing in a large, engineering-heavy environment.
Collaboration & Communication Strong ability to collaborate across engineering, product, and operations teams.
Clear and adaptable communication style for both technical and non-technical audiences.
Proactive attitude — someone who recognizes opportunities, experiments, and independently delivers value.

Responsibilities

Automation & Tooling Own and evolve our automation ecosystem, including Python-based scripts and Jenkins pipelines that drive core business operations.
Build and maintain ETL pipelines that connect, transform, and deliver data from multiple systems (e.g., Jira, internal databases, reporting tools).
Develop, improve, and maintain internal tools — including our status manager, roadmap tool, and notification systems that generate automated Slack and email communications.
Implement monitoring, testing, and reliability guidelines across automations and data flows.
AI-Enabled Operations Leverage large language models (LLMs) to streamline workflows, generate insights, and improve operational efficiency.
Experiment with and implement AI-assisted automation for data summarization, issue classification, and personalized communications.
Share knowledge and build frameworks for scaling AI use across the team.
Data Infrastructure & Reporting Manage and optimize provisioned databases housing critical operational and reporting data.
Partner with data consumers to develop accessible and accurate data models that enable cross-org insights.
Collaborate with analytics teammates to ensure dashboards and reporting tools reflect the latest data and structure.
Operational Excellence See opportunities to automate repetitive tasks, enhance data integrity, and improve transparency across systems.
Drive technical projects end-to-end, from concept to implementation, ensuring reliable, maintainable solutions.
Contribute to long-term platform scale by improving tooling, processes, and documentation.