Job Description
We’ll Trust You To:*Please note we use years of experience as a guide but we certainly will consider applications from all candidates who are able to demonstrate the skills necessary for the role.
- Enable Technical Discussions: Facilitate high-level technical discussions to ensure alignment with system design, scalability, and best practices.
- Champion AI & Automation: Identify and advocate for the inclusion of AI and Machine Learning within the data lifecycle to automate manual processes and increase overall system, process, and collaboration efficiency.
- Ensure System Alignment & Deduplication: Audit existing data models and infrastructure to promote interoperability and prevent the redundant creation of pipelines where existing architectures should be utilized.
- Orchestrate Technical Delivery: Coordinate the work of ontologists, platform integration engineers, data practitioners, and software engineers to ensure that commitments to users are realistic and met.
- Design Interconnected Models: Develop interconnected data models and knowledge organization structures (taxonomies/ontologies) that elegantly conceptualize knowledge across multiple domains.
- Manage Complex Programs: Lead the planning, execution, and delivery of complex, cross-functional programs, ensuring all milestones and deliverables are met on time and in-scope.
- Bridge Product and Technical Leadership: Act as the primary link between product owners, technical leads, and individual contributors, keeping all parties aligned with the goal and removing obstacles to collaboration.
You’ll Need to Have:
- Stakeholder Management: Proven experience managing multiple stakeholders, deadlines, and competing priorities across a complex organization.
- Technical Mastery: An appreciation of data management, including data modeling, metadata management, and the software development life cycle (SDLC).
- System Design & Delivery: Demonstrated ability to translate business requirements into program objectives and work across teams to deliver on the design.
- Communication: Excellence in communicating complex technical topics (including AI/ML concepts) with appropriate scope to varying audiences, from leadership to individual contributors.
We’d Love to See:
- AI/ML Inclusion: Experience identifying use cases for Large Language Models (LLMs) or Generative AI to enhance data discovery, classification, or metadata generation.
- Technical Tooling: Experience with collaborative platforms such as MIRO and JIRA, and a passion for championing new collaborative tools (AI-assisted or otherwise) to improve team efficiency and transparency.
- Semantic Technology Exposure: Knowledge of metadata systems, semantic technologies, linked data, and/or knowledge graphs.
- Industry Standards: Understanding of Data Governance and Data Management, supported by industry certifications such as DAMA CDMP or DCAM.
- FAIR Principles: Ability to enable the capture and storage of Bloomberg data in a manner that is findable, accessible, interoperable, and reusable.