Technical Project Manager

Role overview

The position supports technical project leaders in executing complex data and software initiatives, with a focus on engineering, analytics, ML/AI, and data platform engagements. The role blends agile facilitation, stakeholder coordination, and lightweight program management to keep distributed teams aligned and delivery-focused. It suits someone who can translate between technical contributors and business stakeholders while keeping pace with fast-moving, ambiguous work.

• Run agile ceremonies and meeting logistics, capture decisions and action items, and circulate notes promptly to keep cross-functional teams aligned.
• Track dependencies, deadlines, and follow-ups across technical leads, engineers, and client stakeholders, escalating risks and clearing roadblocks to maintain momentum.
• Foster collaboration across distributed groups by reducing friction in communication between engineering teams and business partners.
• Champion lightweight agile practices such as visual boards, retrospectives, and feedback loops that improve transparency and predictability.
• Identify risks and blockers early, partnering with technical contributors to design mitigations and keep the engagement on track.

• Hands-on experience working with IT or technology teams inside agile environments, including serving as a Scrum Master or facilitating ceremonies across multiple squads.
• Demonstrated stakeholder management and negotiation skills, with a record of influencing change and building durable relationships with technical and business audiences.
• Strong planning, organizational, and time-management abilities, supported by sharp problem-solving and critical-thinking skills.
• Comfort operating in ambiguous situations while maintaining a positive, resourceful, and proactive mindset.
• Advanced written and spoken English, including the ability to translate between technical and non-technical stakeholders.
• Background managing data or software projects, ideally in analytics, machine learning, AI, or data engineering contexts.

• Familiarity with cloud platforms commonly used for data workloads such as Databricks, AWS, GCP, or Azure.
• Agile or project management certifications (CSM, PSM, or equivalent).
• Working knowledge of collaboration and tracking tools such as Jira, Confluence, Asana, or Trello.
• Bachelor's degree in Information Technology, Business, or a related field.

• An environment centered on modern data engineering and applied AI work, with opportunities to grow into broader program leadership responsibilities.
• A collaborative culture that emphasizes knowledge sharing, cross-team learning, and customer-impact-driven delivery.