IT Project Manager
Job in
Charlotte, Mecklenburg County, North Carolina, 28245, USA
Listed on 2026-03-08
Listing for:
Eliassen Group
Full Time
position Listed on 2026-03-08
Job specializations:
-
IT/Tech
Data Engineer, IT Project Manager, Data Science Manager, Business Systems/ Tech Analyst
Job Description & How to Apply Below
- Own end-to-end delivery for multiple concurrent data initiatives across two teams.
- Establish and manage a structured work intake process with clear scope, requirements, and acceptance criteria.
- Develop and maintain project plans, timelines, and forecasts, adjusting for changing priorities and dependencies.
- Drive predictable delivery through proactive risk identification, mitigation planning, and timely issue escalation.
- Partner with product owners, engineering leads, and business stakeholders to prioritize work based on value, capacity, and dependencies.
- Facilitate trade-off discussions and communicate delivery impacts and constraints.
- Manage and track external and cross-team dependencies to maintain alignment across platforms and teams.
- Facilitate Agile ceremonies including daily standups, sprint planning, backlog refinement, reviews, and retrospectives.
- Ensure Agile best practices while keeping teams pragmatic and outcome-focused.
- Remove blockers and enable efficient and sustainable team operations.
- Own outbound communications to stakeholders and leadership, including status, forecasts, risks, and milestones.
- Create clear artifacts such as dashboards, timelines, RAID logs, and executive summaries.
- Serve as a central coordinator between technical teams and non-technical partners.
- 7+ years of technical project or program management experience, preferably supporting data or platform teams.
- Proven success managing multiple teams and complex delivery roadmaps.
- Strong understanding of Agile and Scrum methodologies.
- Excellent organizational, communication, and stakeholder management skills.
- Ability to translate between technical and business audiences.
- Experience managing dependencies, risks, and delivery forecasts in dynamic environments.
- Fluency in modern data platforms and architectures, including data products and data platforms.
- Familiarity with AWS data services such as Glue, DMS, Lambda, and Amazon Aurora (Postgre
SQL). - Understanding of data processing using PySpark and Python.
- Experience with streaming and messaging technologies including Kafka and batch or streaming data pipelines.
- Experience with analytics and BI tools such as Qlik.
- Experience working with data engineering, analytics, or data platform teams (preferred).
- Familiarity with cloud-native data architectures on AWS (preferred).
- Experience supporting both streaming and batch data processing (preferred).
- Background as a technical contributor in engineering, data, or analytics (preferred).
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