Technical Project Manager

Technical Project Manager:

We are seeking a highly skilled Technical Project Manager to lead and coordinate data-driven projects from inception to completion. This role involves collaborating with cross-functional teams, ensuring timely delivery of project milestones, and effectively communicating project status and insights to stakeholders.

Key Responsibilities:

Project Leadership:

• Define project scope, goals, and deliverables in collaboration with stakeholders.
• Develop detailed project plans, timelines, and resource allocation strategies.
• Ensure projects are completed on time, within scope, and within budget.

Stakeholder Management:

• Act as the primary point of contact for project stakeholders.
• Regularly communicate project progress, risks, and issues to stakeholders.
• Gather and incorporate feedback from stakeholders to refine project objectives.

Data Strategy:

• Collaborate with data teams to identify data needs and ensure quality data collection and management.
• Analyze and interpret data to drive business decisions and strategies.

Risk Management:

• Identify potential project risks and develop mitigation strategies.
• Monitor project progress and implement corrective actions as necessary.

Reporting and Documentation:

• Create comprehensive project documentation, including reports, dashboards, and presentations.
• Track project performance and report on key metrics to senior management.

Qualifications:

• Bachelor's/masters in computer science, Engineering, or related field.
• Proven experience in project management, particularly in Data Engineering, Data Products, Data Apps.
• Strong understanding of Data Full Stack.
• Experience with project management tools.
• Excellent communication and interpersonal skills.
• Strong analytical and problem-solving abilities.
• Ability to manage multiple projects simultaneously and meet deadlines.
• PMP, CSM, or equivalent certification preferred.

Preferred Skills:

• Experience in Agile methodologies.
• Familiarity with machine learning and statistical modelling.
• Knowledge of cloud computing platforms (e.g., AWS, Azure, Google Cloud).