Sr. Technical Project Manager

Hazel Seybert Consulting•Chicago, IL

7d•Hybrid

About The Position

We are seeking a high-energy, pragmatic, and cloud-fluent Technical Project Manager for a 6-month contract (with strong potential for extension). Our client is entering Phase 2 of an enterprise-wide initiative to scale their centralized data repository—the ultimate "source of truth" across the enterprise that will eventually fuel corporate reporting, and insights. This role bridges the gap between technical execution and project coordination. You will sit directly over two small, data engineering pods (4–5 developers total) and a Senior System Architect to guide, remove roadblocks, and keep deliverables strictly on track. Role can be located in : IL, MI, IA, GA, NM or SC

Requirements

5-7+ years of technical project management or Scrum Master experience heavily focused on enterprise data architecture, data warehousing, or data foundation projects.
Hands-on experience managing projects deployed on major cloud platforms. While the client’s architecture is rooted in Google Cloud Platform (GCP), proven experience successfully standing up or scaling enterprise platforms is highly transferable and welcomed.
Solid understanding of data pipelines (ETL/ELT), database management (SQL), data mapping among disparate legacy systems (e.g., SAP, Salesforce), and data governance initiatives.
Expert proficiency in Agile/Scrum frameworks, sprint planning, and utilizing modern project tracking tools (Jira, Confluence, Azure DevOps, etc.).
Ability to work hybrid on-site in the Chicago, IL area. The team operates in-office Tuesday through Thursday; local candidates or those capable of regular, self-managed travel during core office days are strongly preferred.

Nice To Haves

Certified ScrumMaster (CSM), Professional Scrum Master (PSM), or Project Management Professional (PMP) credentials are a significant plus.

Responsibilities

Facilitate daily stand-ups, end-of-day scrum check-ins, and manage structured 2-week sprint cycles across two parallel data engineering pods.
Shepherd the ingestion and pipelining of new enterprise data sources (e.g., integrating SAP, Salesforce) into the centralized cloud data foundation.
Coordinate the deepening and optimization of established data domains (e.g., customer, inventory, pricing) with a heavy focus on data quality, cleansing, and governance.
Serve as the tactical liaison between the core engineering pods, system architecture, and 5–6 cross-functional business stakeholders or subject matter experts.
Proactively identify technical roadblocks, map system dependencies, and deliver actionable, data-driven recommendations and status updates to the internal leadership triad (Data Architecture, Insights & Intelligence, and Business Leadership).
Drive a culture of immediate resolution—jumping in a room or sending a quick chat to resolve issues dynamically rather than drawing out decisions over email.