Remote Data Engineering PM — Cloud Migrations & Analytics Delivery

LucyRx

Northern (KY)

Hybrid

USD 90,000 - 130,000

Full time

5 days ago

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Job summary

LucyRx is seeking a Technical Project Manager to bring structure, clarity, and momentum to the data engineering organization as we modernize our data platform and migrate Oracle systems to the cloud. You will connect business stakeholders with engineers, manage intake, scoping, and delivery, and protect the team from scope creep while ensuring clear communication.

You do not write code but must understand data pipelines, ETL/ELT, data warehousing, and analytics workflows to guide projects.

Qualifications

Bachelor's degree in Computer Science, Information Systems, Business, or a related field, or equivalent experience.
5+ years of project management experience, with at least 3 years managing technical data or engineering projects.
Demonstrated experience working with data engineering, analytics, or BI teams in a project management capacity.
Strong understanding of data concepts: pipelines, ETL/ELT, data warehousing, and reporting workflows.
You do not need to build these things, but you need to understand them well enough to scope and manage them.
Proficiency with Agile, Scrum, or Kanban delivery frameworks.
Comfortable running ceremonies, managing sprints, and adapting process to what the team actually needs.
Experience with project and backlog management tools such as Jira, Azure DevOps, Confluence, or similar.
Excellent written and verbal communication skills.
You can write a crisp status update, run a focused meeting, and have a direct conversation when something is off track.
Strong organizational skills and attention to detail.
Comfortable operating in a fast-moving, ambiguous environment where processes are still being built.

Responsibilities

Own the intake process for data engineering requests across the organization, including business intelligence, pipeline development, Oracle database work, and analytics enablement.
Partner with business stakeholders in clinical operations, finance, product, and reporting to gather and define requirements with enough clarity that engineering can scope and execute without constant back-and-forth.
Translate business needs into well-defined technical requirements. Push back when requirements are vague, incomplete, or likely to change mid-execution.
Maintain a clear, prioritized view of incoming requests and help leadership make informed tradeoff decisions.
Facilitate scoping and estimation sessions with engineering leads. Ensure work is broken down to a level of detail that allows for reliable delivery commitments.
Identify dependencies, risks, and assumptions early and surface them before work begins rather than after it derails.
Maintain realistic delivery timelines that account for team capacity, complexity, and competing priorities.
Own the day-to-day delivery cadence for active data engineering work.
Run standups, facilitate sprint planning and retrospectives, and keep the team moving.