Senior Associate Data Integration Project Manager

Company description

Publicis Sapient is a digital transformation partner helping established organizations get to their future, digitally enabled state, both in the way they work and the way they serve their customers. We help unlock value through a start-up mindset and modern methods, fusing strategy, consulting, and customer experience with agile engineering and problem-solving creativity. United by our core values and our purpose of helping people thrive in the brave pursuit of next, our 20,000+ people in 53 offices around the world combine experience across technology, data sciences, consulting, and customer obsession to accelerate our clients’ businesses through designing the products and services their customers truly value.

The PM leads planning, prioritization, and delivery for the Data Integration and Analytics team. This role connects business needs, analytics goals, and data engineering execution.

The ideal candidate has experience managing delivery for data integration, analytics, business intelligence, data engineering, or data platform teams. They should be comfortable working with both client/business stakeholders and technical data teams. They do not need to be a hands-on data engineer or architect, but they must be technically fluent enough to ask the right questions, clarify dependencies, manage tradeoffs, and keep delivery moving.

• Manage intake, prioritization, sequencing, and visibility for data integration and analytics work.
• Define data and analytics goals based on understanding and partnership with clients, product teams, and technical teams.
• Translate business needs into clear, actionable delivery work, including backlog items, priorities, dependencies, acceptance criteria, and delivery plans.
• Coordinate delivery across data pipelines, ETL/ELT processes, data marts, data migration support, data quality, data freshness, pipeline observability, and performance optimization.
• Help identify opportunities to use business intelligence, analytics, curated datasets, and improved data access patterns to improve performance, services, and decision-making.
• Champion data-driven practices and promote a business intelligence mindset across stakeholders.
• Drive adoption of governed BI tools, reporting standards, reusable data products, and scalable analytics practices.
• Guide power users away from direct querying of transactional databases and toward reliable, governed, reusable analytics solutions.
• Clarify when migration work should be handled by product teams versus when it requires central Data Integration support.
• Surface risks, blockers, ownership gaps, and cross-team dependencies early.

• 5+ years of experience in Agile project management, Scrum, or SAFe methodologies.
• Data delivery leadership:
  Experience managing delivery for data integration, analytics, BI, data engineering, or data platform teams.
• Data integration fluency:
  Practical understanding of pipelines, ETL/ELT, data marts, source-to-target movement, transformation logic, migration support, and downstream consumption.
• Data quality and freshness mindset:
  Understands that “done” means data is accurate, complete, timely, trusted, and usable by downstream consumers.
• Pipeline operations awareness:
  Familiarity with pipeline monitoring, failures, delays, refresh schedules, observability, reliability, and performance optimization.
• Business and client translation:
  Ability to partner with stakeholders to define analytics goals, understand operational needs, and translate them into actionable delivery work.
• BI adoption and governance:
  Ability to promote BI best practices, governed reporting, reusable datasets, and scalable analytics solutions instead of one-off data pulls or direct transactional queries.
• Backlog and prioritization discipline:
  Ability to manage intake, prioritization, dependencies, acceptance criteria, sequencing, and delivery visibility.
• Cross-functional communication:
  Ability to coordinate across product, analytics, engineering, infrastructure, business stakeholders, and external data consumers.
• SQL and data literacy:
  Does not need to code daily, but…