Are you an accomplished senior project manager looking to apply your level of expertise to drive meaningful projects and portfolios of work forward. Specifically, help support client project work across multiple practices ranging from Data Analytics, Data Engineering, Decision Sciences and Analytics Strategy.
Aimpoint Digital is a premier global date and AI consulting firm with a mission to drive business value for clients through expertise in data strategy, data analytics, decision sciences, and data engineering and infrastructure. We're a dynamic team committed to solving our client's most critical business challenges in partnership with the industry's most innovative cloud and data technology providers. What sets us apart is our approach: we start by truly listening, then craft tailored solutions powered by modern technologies, which are delivered by our passionate consulting experts. Joining our team means working alongside some of the brightest minds in data and AI consulting to solve meaningful problems for our clients.
You will:
- Become a trusted advisor working together with our clients, from data owners and analytic users to C-level executives
- Manage a diverse set of projects extending across multiple disciplines
- Serve as the primary client-facing lead for project planning, delivery, risk management, and communication
- Own project governance, including status reporting, issue/risk escalation, and stakeholder engagement
Specific technical qualifications as follows:
- CAPM or PMP certified preferred; CSM, SAFe, or equivalent Agile certifications a plus. Demonstrated proficiency across Hybrid, Waterfall, and Agile methodologies with the ability to select and tailor the right framework for each engagement
- Working knowledge of the modern data ecosystem, including cloud data platforms (Snowflake, Databricks, GCP/BigQuery), data pipelines, and data warehousing concepts, sufficient to engage credibly with data engineers, architects, and data scientists
- Experience managing data migration and platform modernization engagements, including planning for data validation, cutover activities, and coordination between legacy and target environments
- Familiarity with AI and machine learning project delivery, including the iterative and experimental nature of model development, proof-of-concept phases, and the path from pilot to production
- Experience supporting data analytics engagements end to end, including discovery, requirements gathering, KPI and metric definition, and coordination of dashboard development in tools such as Tableau, Power BI, or Looker
- Strong stakeholder management and communication skills, including experience translating technical data concepts for executive audiences and delivering executive-level reporting