Technical Project Manager

at  Blumie

Blumie is a leading data consultancy firm, committed to delivering fast and effective data solutions to businesses across various industries. We are dedicated to empowering businesses through data science, analytics, and AI, optimizing costs and maximizing revenue. At Blumie, we value innovation and seek passionate individuals who are eager to transform data into strategic decisions.
We are seeking a Technical Project Manager with proven experience in managing data projects to lead and coordinate multiple initiatives for one of our largest clients in the data and AI sector. The ideal candidate should have a solid background in Computer Science or Engineering, with experience overseeing projects involving data warehouses, data analysis, and advanced techniques such as BI, statistics, and data science/machine learning.

REQUIREMENTS:

• Degree in Computer Science, Engineering, or a related field.
• Over 3 years of experience in project management within data teams, with a proven track record in coordinating projects involving data warehouses, data analysis, and advanced techniques such as BI and data science/machine learning.
• experience with SQL, Python, and other data technologies is desirable, although coding is not required for this position.
• Demonstrated ability to manage teams of developers and coordinate work across different technical specialties.
• Advanced English, both written and spoken, is essential for communication with global teams and stakeholders.

• Project Management: Plan, execute, and close data projects, ensuring timely delivery and within budget. Coordinate activities between cross-functional teams and manage stakeholder expectations.
• Team Supervision: Lead and oversee the work of data engineers, data analysts, and frontend developers, ensuring that all team members work effectively and efficiently towards project goals.
• Communication: Act as the primary point of contact for projects, facilitating communication between teams and ensuring clarity in project expectations and requirements.
• Resource Management: Allocate tasks and resources effectively, monitor progress, and resolve any issues or obstacles that may arise during the project lifecycle.
• Data Solutions Implementation: Ensure the correct integration of data warehouse solutions, BI, and data analytics into projects, working closely with technical teams to ensure solutions meet specified requirements.