Lead Technical Program Manager – Enterprise Data

About the Job:
As a Lead Technical Program Manager, you will plan, coordinate, and actively manage the data delivery plans for complex, cross-functional technical solutions that span multiple technical products.

Do you have the right skills and experience for this role Read on to find out, and make your application.

You will be responsible for managing the end-to-end roadmap, ensuring all necessary changes to technical products are executed in support of initiative outcomes.

In this role, you will play a key role in overseeing the development and optimization of data pipelines and integrating AI capabilities to enhance data-driven decision-making across the organization.

What You’ll Do:
Lead and align one or more large, complex initiatives consisting of multiple efforts, with a focus on data delivery.

Establish strong connections across teams and work streams to identify and facilitate interdependencies and establish sequencing.

Create a cohesive, unified plan to achieve program objectives, ensuring alignment with the interim and target state enterprise data strategy.

Oversee the development and optimization of data pipelines, ensuring journey towards target state and support of analytics and AI initiatives.

Identify, assess, and mitigate program risks and issues, proactively removing impediments to ensure smooth project execution.

Fostering a culture of continuous improvement and collaboration.

Skills You Have:
Bachelor’s degree in Business Administration, Computer Science, Information Systems, or a related field, or an equivalent combination of education and work experience.

Minimum 6 years of professional experience, with at least five years of project management within technology and/or business functions.

Demonstrated experience with program management methodologies and governance, with a strong emphasis on managing data dependencies and sequencing.

Proficiency in project management methodologies and SDLC, with working knowledge of project management/agile tools.

Strong “influence without authority†management skills.

Deep understanding of software development, testing, and implementation, as well as technical concepts related to data management and AI.

Exposure to managing data pipelines and integrating AI tools to enhance data processing and analytics capabilities.

Ability to work closely with engineers, product managers, and business leaders, fostering collaboration and alignment.

Experience managing large-scale, cross-functional initiatives using various delivery methodologies (e.g., waterfall, agile, lean, scrum).

Strong analytical and problem-solving skills, with a focus on identifying and resolving complex data-related issues.

Intellectual curiosity and a desire to delve into details, learn, ask questions, and become the "go-to expert" on data-related concepts and topics.

Proven ability to lead highly visible multidisciplinary project teams or initiatives, providing thought leadership and strategic direction.

Capability to solve unique problems with broad impact on the business, requiring conceptual and innovative thinking to develop solutions.

Ability to impact the direction and resource allocation for programs, projects, or services, working within general department policies and industry guidelines.

Excellent communication skills, with the ability to explain difficult or sensitive information and build consensus across diverse teams.

Additional Skills We’d Love:
Experience in enterprise data management, with a focus on upstream data integration and delivery.

Familiarity with data governance practices and data quality management.

Understanding of cloud-based data platforms and AI tools.

#LI-Hybrid Compensation Range:
Pay Range
- Start: $ Pay Range
- End: $ Geographic Specific Pay Structure:
Structure 110: $ USD
- $ USD Structure 115: $ USD
- $ USD We believe in fairness and transparency.

It’s why we share the salary range for most of our roles.

However, final salaries are based on a number of factors, including the skills and experience of the candidate; the current market; location of the candidate; and other factors uncovered in the hiring process.

The standard pay structure is listed but if…