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AI & Data Project Manager

Bbenergy · Athens, Greece
// classified as
Other (Adjacent or hard to classify.)
posted
1d ago
location
Athens, Greece
languages
tools
azure
> stack
azure
> description

Purpose of the Role



  • Drive BB Energy’s AI and data transformation across Data Science, IT, Operations, Risk, and commercial teams, helping build the next generation of AI-enabled trading, operations, risk, and analytics capabilities.
  • Operate at the intersection of AI transformation, enterprise analytics, Microsoft Fabric & Azure, data governance, automation, executive strategy, and operational delivery.
  • Work directly with senior leadership to coordinate high-impact initiatives that modernise how BB Energy manages data, reporting, decision-making, and operational workflows.
  • Help shape the company’s AI and analytics operating model and deliver measurable impact across the organisation — building the future operating model of AI, analytics, and data-driven decision making at BB Energy.


Accountabilities/Key Result Areas



  • Program & Project Delivery: Lead end-to-end delivery of AI and data initiatives. Coordinate timelines, milestones, risks, dependencies, and budgets. Drive execution across multiple parallel workstreams and ensure successful delivery from concept through production rollout.
    • Cross-Functional Coordination: Act as the bridge between Data Science, IT, PMO, Operations, Risk, Trading, and external vendors. Facilitate alignment between business and technical stakeholders and drive accountability and execution across teams.
    • AI & Data Platform Transformation: Coordinate initiatives across Microsoft Fabric, Azure, Power BI, Purview, and enterprise data governance. Support the evolution toward centralised, governed, scalable analytics platforms.
    • Governance & Executive Reporting: Build executive-level reporting and steering processes. Maintain RAID logs, KPIs, status reporting, and governance structures. Track business value realisation and operational impact, and provide leadership with clear visibility across strategic initiatives.
    • Vendor & Partner Management: Coordinate delivery with Microsoft and implementation partners. Help structure and govern external delivery engagements and ensure alignment between vendors and internal teams.
    • Strategic Initiative Scope: Lead and coordinate initiatives such as enterprise AI transformation programs, AI Agents and Generative AI initiatives, Microsoft Fabric implementation, Power BI enterprise reporting, Azure data platform modernisation, data governance and lineage, risk and exposure analytics, operational workflow automation, executive dashboards and KPI frameworks, and data warehouse and integration projects.



    Performance Behaviours



    • Highly organised and execution-oriented — proactive and ownership-driven, with a track record of getting things done.
    • Technically curious and commercially aware — comfortable operating in technical environments while keeping commercial outcomes in focus.
    • Comfortable operating in ambiguity and able to simplify complexity for diverse audiences.
    • Confident engaging senior stakeholders and facilitating alignment between business and technical teams.
    • Enjoys building structure where structure does not yet exist, and is energised by shaping how AI and analytics are operationalised inside a global business.


    Skills and experience



    • Experience: 5+ years in AI/Data program management, analytics transformation, technology consulting, or enterprise delivery.
    • Proven track record delivering enterprise-scale data or AI initiatives in complex, cross-functional environments.
    • Technical understanding: Strong familiarity with several of the following: Microsoft Azure, Microsoft Fabric, Power BI, data warehousing, data governance, AI / Generative AI, analytics platforms, and data engineering concepts. The role does not require an engineering background, but the candidate should be comfortable operating in technical environments and coordinating technical teams.
    • Strongly preferred: Consulting background (e.g. EY, Deloitte, Accenture, PwC, KPMG).
    • Experience with enterprise transformation programs and exposure to executive stakeholders.
    • Background in energy, commodities, trading, logistics, or financial services environments.