Senior Product Software Engineer - Data Platform

Disney Entertainment and ESPN Product & Technology Technology is at the heart of Disney’s past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more – all working to build and advance the technological backbone for Disney’s media business globally. The team marries technology with creativity to build world‑class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses. We are Storytellers and Innovators. Creators and Builders. Entertainers and Engineers. We work with every part of The Walt Disney Company’s media portfolio to advance the technological foundation and consumer media touch points serving millions of people around the world. Reasons to work here Building the future of Disney’s media: Our Technologists are designing and building the products and platforms that will power our media, advertising, and distribution businesses for years to come. Reach, Scale & Impact: More than ever, Disney’s technology and products serve as a signature doorway for fans’ connections with the company’s brands and stories. Disney+, Hulu, ESPN, ABC, ABC News…and many more. These products and brands – and the unmatched stories, storytellers, and events they carry – matter to millions of people globally. Innovation: We develop and implement groundbreaking products and techniques that shape industry norms and solve complex and distinctive technical problems. Ad Platforms is responsible for Disney’s industry‑leading ad technology and products – driving advertising performance, innovation, and value in Disney’s sports, news, and entertainment content, across all media platforms. Job Summary We’re hiring an Innovative Data Platform Automation Engineer to cut manual toil and raise reliability across our data platform—through better monitoring and the tools that support it. In this role you will design and build services and internal tooling that keep production data pipelines healthy, with a strong focus on automating monitoring, speeding up pipeline debugging, and maintaining SLAs. You will also help develop AI agents and workflows that assist with debugging complex pipelines by connecting runtime signals to our knowledge base, and that work with data quality services to surface, explain, and triage data issues faster. Responsibilities Automate Data platform Operations Automate recurring operational work Convert runbooks and ad‑hoc fixes into version‑controlled automation (Python/Go CLI, scheduled jobs, CI‑driven checks, or lightweight services) and traceable execution. Partner with data engineers on the real system Model DAG dependencies, SLAs/SLO touchpoints, and orchestration. Prioritize tooling that accelerates incident response: dependency/lineage views, data freshness monitors, schema/drift checks. Build agentic workflows for faster isolation Implement LLM‑assisted triage services that fuse metrics, logs/traces, orchestrator task metadata, data quality rules, and incident history with dependency aware evaluations to propose ranked hypotheses and verification steps (e.g. partition gaps, late upstream, contention, bad deploy, contract mismatch). Integrate via webhooks/APIs into on‑call workflows (PagerDuty/Slack/Jira) with guardrails. Basic Qualifications Bachelor’s degree in computer science, engineering, or related technical field (master’s preferred), or equivalent experience. 5+ years in data platform engineering, or data operations (DataOps/SRE‑style), with demonstrable experience shipping AI‑assisted automation and internal tool expertise. Strong Python: application/library development, testing (unit/integration), packaging and distribution, and production‑minded practices (logging, config, error handling, observability hooks as appropriate). APIs and integration experience: experience building services, internal SDKs/CLIs, or platform components consumed by multiple teams. LLM engineering: hands‑on use of LLM APIs (e.g., OpenAI, Anthropic) and orchestration with frameworks such as LangChain or LangGraph (or equivalent), including prompt/tool design, evaluation, and safe production patterns (permissions, guardrails, cost/latency controls). Agentic systems in practice: shipped reusable agents, workflows, or libraries that improved debugging, triage, or automation—and were adopted beyond a single team. Cross‑functional execution: strong communication and stakeholder management across infrastructure, data engineering, security, and product; comfortable translating ambiguous operational pain into measurable platform outcomes. Preferred Qualifications Strong software engineering experience to build tools and services with Python or GoLang. Understanding of data platform such as Databricks, Snowflake and ETL tools such as Spark. Previous experience in a developer enablement role (platform engineering, frameworks, SDKs) where reusable components accelerated adoption across large organizations. The hiring range for this position in Los Angeles, California is $141,900 to $190,300 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job‑related knowledge, skills, and experience among other factors. A bonus and/or long‑term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered. #J-18808-Ljbffr