Technical Project Manager

We are seeking an agile-focused Technical project manager with a strong data engineering background to lead scrum while guiding a small pod of data engineers. In this role, your primary responsibility is operational excellence—acting as a dedicated Scrum Master to facilitate agile ceremonies, eliminate blockers, protect team capacity, and optimize delivery velocity for our client. While this is heavily a Scrum Master role, your data background will allow you to serve as a technical sounding board for the engineers. You will champion the agile execution of migrating our legacy big data environment to a modern AWS/Databricks infrastructure, orchestrating the rollout of intelligent AI agents (utilizing Anthropic Claude), and coordinating technical support for our downstream Tableau business intelligence layer. Core Responsibilities Agile Scrum Master Ownership: Serve as the dedicated Scrum Master for the client’s data engineering team. Own all agile ceremonies—including daily standups, sprint planning, backlog grooming, and retrospectives—while actively tracking velocity, burn-down metrics, and managing team capacity. Delivery Roadmapping & Operational Execution: Partner with business and technical stakeholders to translate high-level migration roadmaps and AI initiatives into a well-structured, prioritized product backlog of actionable user stories. Engineering Shielding & Blocker Removal: Actively identify and eliminate organizational, infrastructure, or technical dependencies that stall development. Shield the engineers from ad-hoc requests and scope creep to keep the sprint focused. Agile Expertise: Proven track record of successfully running scrum frameworks for highly specialized technical teams. Data Domain Familiarity: Strong conceptual understanding of big data architectures (Apache Spark, Hadoop, Hive) and cloud platforms ( AWS and Databricks ). You don't need to write the code, but you must thoroughly understand the tech stack to effectively groom the backlog and challenge story sizing. AI/LLM Project Exposure: Practical experience or strong conceptual literacy managing agile sprints that involve LLM integrations (specifically Anthropic Claude ), AI workflows, or data pipelines feeding vector databases. BI Lifecycle Awareness: Understanding of how backend data pipelines interface with downstream business visualization tools like Tableau , ensuring sprint goals align with business-facing reporting needs. Operational Leadership: Outstanding communication skills, with the ability to run high-efficiency scrum processes, resolve team conflicts, build data-driven delivery metrics, and clearly convey timeline risks to stakeholders. Education: Bachelor’s degree in Business Information Systems, Computer Science, Project Management, Data Analytics, or a related field, or equivalent practical experience.