Architect

InnoSoul•Austin, TX

4d•Hybrid

About The Position

This role supports a Technical Project Manager for a data engineering project with an AI adoption program. The position involves managing cross-functional coordination, tracking deliverables, supporting platform and data engineering initiatives, and ensuring alignment between business, engineering, and AI stakeholders. Familiarity with cloud platforms, data pipelines, and AI/ML adoption efforts is highly desirable, along with strong communication and organizational skills. The role requires 8 or more years of experience, relies on experience and judgment to plan and accomplish goals, independently performs a variety of complicated tasks, and a wide degree of creativity and latitude is expected. The individual will be responsible for the planning, coordination, requirements gathering, business analysis, specifications development, project planning, project monitoring, and project status reporting and system implementation of moderate to complex business solutions. Project Management Professional (PMP) certification is required.

Requirements

10+ years of experience leading technical projects or programs in data, analytics, and cloud environments.
10+ years of experience leading data architecture, data modeling, and data warehousing initiatives from planning through delivery.
10+ years of experience managing business intelligence, big data, and analytics projects in complex enterprise environments.
10+ years of experience supporting healthcare data initiatives.
Working knowledge of SQL and database technologies to support project planning, estimation, and issue resolution.
Strong communication skills with the ability to translate complex technical concepts for business and executive audiences.
Proven leadership skills managing cross-functional teams, vendors, and complex project timelines.
Strong collaboration skills to work effectively with data engineers, developers, analysts, and business partners.
10+ years of experience defining project scope, objectives, milestones, timelines, and success metrics.
10+ years of experience with project budgeting, forecasting, resource planning, and financial status reporting.
Proficiency with project management tools such as Jira, Azure DevOps, MS Project, or Smartsheet.
Strong documentation skills for project plans, charters, schedules, and lessons learned.
Working knowledge of cloud platforms, data systems, or enterprise applications.
Proactive leadership style with strong attention to detail and ability to work independently.
Project Management Professional (PMP) certification is required.

Nice To Haves

Familiarity with FHIR, CCDA, and HL7 standards.
Familiarity with healthcare or other regulated environments, including compliance, security, and data governance concepts.
PMP, PgMP, PMI-ACP, SAFe, or similar project management certification preferred.
Healthcare industry experience preferred.
Fundamental understanding of information management principles, IT processes, SDLC, architecture, and enterprise technologies.
Strong consulting and facilitation skills.
Customer-focused communication skills with the ability to engage all levels of the organization.
Proactive leadership style with strong attention to detail and ability to work independently.
Experience supporting AI, advanced analytics, or digital transformation initiatives at the program or project level.
TOGAF, Cloud Solution Architecture, or Azure/AWS/GCP certifications preferred.

Responsibilities

Leading technical projects or programs in data, analytics, and cloud environments.
Leading data architecture, data modeling, and data warehousing initiatives from planning through delivery.
Managing business intelligence, big data, and analytics projects in complex enterprise environments.
Supporting healthcare data initiatives.
Translating complex technical concepts for business and executive audiences.
Managing cross-functional teams, vendors, and complex project timelines.
Collaborating effectively with data engineers, developers, analysts, and business partners.
Defining project scope, objectives, milestones, timelines, and success metrics.
Managing project budgeting, forecasting, resource planning, and financial status reporting.
Documenting project plans, charters, schedules, and lessons learned.
Coordinating technical projects or programs in data, analytics, and cloud environments.
Coordinating data architecture, data modeling, and data warehousing initiatives from planning through delivery.
Coordinating business intelligence, big data, and analytics projects in complex enterprise environments.
Coordinating healthcare data initiatives.
Coordinating project budgeting, forecasting, resource planning, and financial status reporting.
Coordinating project plans, charters, schedules, and lessons learned.
Tracking deliverables.
Supporting platform and data engineering initiatives.
Ensuring alignment between business, engineering, and AI stakeholders.