Job summary
Job post source
This job is directly from STV
Job overview
The Digital Development Specialist at STV leads digital transformation and PMIS platform implementation to enhance project delivery in infrastructure and transportation programs.
Responsibilities and impact
The role involves leading PMIS implementation, optimizing enterprise systems, applying emerging technologies, coordinating digital solutions, supporting clients in digital transformation, facilitating workshops, integrating data-driven tools, monitoring industry trends, and collaborating with digital experts.
Compensation and benefits
The position offers a salary range of $82,265.06 to $109,686.74 with benefits including health, dental, vision insurance, flexible spending accounts, disability, life insurance, 401(k), retirement counseling, paid time off and holidays, parental leave, continuing education, and professional memberships.
Experience and skills
Requires 3+ years in PMIS or digital advisory in AEC, a bachelor's degree in a related field, hands-on PMIS experience, understanding of AEC projects, and familiarity with technologies like BIM, GIS, Power BI, and cloud platforms; AI and predictive analytics experience is a plus.
Career development
STV encourages diversity and inclusion and supports professional growth through continuing education programs and professional licensure support.
Work environment and culture
STV promotes a culture of diversity, inclusion, fairness, and transparency, reflecting the communities they serve with a supportive work environment.
Company information
STV is a company focused on infrastructure and transportation projects, delivering innovative digital solutions and project management services across multiple US locations.
Team overview
The candidate will join the Digital Advisory department, collaborating with clients, digital product experts, data scientists, and engineers in a cross-functional team environment.
Job location and travel
The role is based in STV offices located in New York, Boston, Dallas, Chicago, or Denver with travel required for client engagements.
Unique job features
The job features leadership in digital transformation using advanced PMIS platforms and emerging technologies like Digital Twin and AI to drive innovation in large-scale infrastructure projects.
Company overview
STV is a leading engineering, architectural, planning, and construction management firm that provides a wide range of services across various sectors, including transportation, infrastructure, buildings, energy, and water. They generate revenue through project-based contracts with public and private sector clients, offering expertise from initial design through to project completion. Founded in 1912, STV has a rich history of delivering high-profile projects and is known for its commitment to quality, innovation, and sustainability. This long-standing reputation makes it a significant player in the industry, providing a dynamic and collaborative work environment.
How to land this job
Tailor your resume to highlight your experience with PMIS platforms such as Kahua, eBuilder, and Procore, emphasizing your role in digital transformation and workflow optimization within the AEC industry.
Focus on showcasing your ability to lead digital strategies, implement emerging technologies like AI and Digital Twin, and collaborate across multi-disciplinary teams to drive project delivery improvements.
Apply through STV's corporate career site and LinkedIn, as well as other job boards where STV may post this position, to maximize your application visibility.
Connect on LinkedIn with professionals in STV's Digital Advisory department or related divisions; open your message by referencing a recent STV infrastructure project or expressing curiosity about their digital transformation initiatives to break the ice.
Optimize your resume for ATS by incorporating keywords from the job description such as 'PMIS implementation,' 'digital transformation,' 'data governance,' 'AI tools,' and specific platform names like 'Kahua' and 'Procore' to pass screening algorithms.
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