Senior Data Engineer (Knowledge Graph) at Docuvera Software Corporation

Wellington, Wellington, New Zealand -

Full Time

Start Date

Immediate

Expiry Date

08 Jun, 26

Salary

0.0

Posted On

10 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Knowledge Graphs, Semantic Modeling, Ontology Design, Entity Resolution, Graph Database Systems, Neo4j, Neptune, Dgraph, Cypher, SPARQL, GraphQL, Federated Knowledge Access, Data Pipelines, RDF, OWL, SKOS

Industry

Software Development

Description

The part you’ll play and impact you'll make A Senior Data Engineer (Knowledge Graph) is responsible for designing, building, and operating Docuvera’s enterprise knowledge foundation. This role represents a deliberate evolution of our data engineering capability toward Enterprise Knowledge Graphs, semantic modeling, and Federated Data Architecture, in direct support of AI-enabled products, agentic workflows, and human decision-making. You will focus on structuring, connecting, and operationalizing enterprise knowledge, turning distributed data, systems, and context into trusted, connected, and usable knowledge that can be consumed consistently by people and AI systems. Your work will ensure that generative AI features, internal tools, and customer-facing capabilities operate from a shared, context-aware understanding of the organization. This is a senior, hands-on Data Engineering role. You will collaborate closely with software engineers, data engineers, UX designers, product managers, solution architects, and business stakeholders, taking a human-centered design (HCD) approach to building knowledge capabilities that are not only technically robust, but genuinely usable and valuable in day-to-day workflows. This role will accelerate Docuvera's product growth by building and operationalizing the enterprise knowledge foundation that powers AI agents and generative AI features. By structuring and connecting distributed data into trusted, context-aware knowledge, the Senior Data Engineer will reduce delivery friction, enable faster and better-informed decision-making across teams, and ensure that both people and AI systems operate from a shared, consistent understanding of the organization — supporting high-quality outcomes for international customers. What you'll focus on As an experienced Senior Data Engineer (Knowledge Graph) with strong semantic modeling skills, including ontology design, entity resolution, knowledge graph construction, and structuring data for AI-enabled products and agentic workflows, you thrive on taking enterprise knowledge systems from concept through to implementation and operation. Highly organized and proactive, you enjoy enabling others by turning distributed, siloed data into trusted, connected knowledge that people and AI systems can rely on. Partner with the CTO, Engineering Leads, Solution Architects, Product Managers, and UX Designers to define and evolve Docuvera's enterprise knowledge and data strategy Design and maintain an Enterprise Knowledge Graph, including schemas, ontologies, and vocabularies using semantic standards (RDF, OWL, SKOS) Model domain concepts, relationships, and constraints in collaboration with subject matter experts across the business Manage the lifecycle of knowledge artifacts, including versioning, evolution, and cross-domain alignment Build and operate graph database systems (Neo4j, Neptune, Dgraph) with optimised queries and APIs (Cypher, SPARQL, GraphQL) at production scale Architect federated knowledge access patterns enabling consistent, governed discovery and use of information across internal and external systems Enable AI agents, chat agents, and agentic workflows to reason and act effectively using shared enterprise context Design and operate data pipelines feeding knowledge systems, with strong practices around quality, observability, and compliance Apply human-centred design principles with UX, Product, and Engineering to build knowledge tools that are genuinely usable in real workflows Deliver production-grade knowledge systems for international customers, while mentoring engineers and driving a high-quality engineering culture What you'll being to the role Technical skills Hands-on experience with knowledge graphs, graph databases, or semantic technologies, or a demonstrated ability to ramp up quickly in this space. Experience designing and querying graph-based systems using graph query languages and APIs. Solid SQL skills and experience working with relational databases as source or integration systems. Experience working with distributed systems, streaming or messaging platforms, and scalable data architectures. Exposure to supporting AI, ML, or generative AI systems by providing structured, reliable, and context-rich data. Proven experience working effectively with cross-functional teams in a complex, evolving environment. Non-technical skills Structured and organized, able to navigate ambiguity and drive delivery in a fast-moving environment Collaborative and cross-functional, with strong stakeholder influence across technical and non-technical audiences A change enabler, helping teams adapt, experiment, and adopt new ways of working High emotional intelligence, with the ability to build trust and lasting working relationships Pragmatic, creative problem-solver focused on high-impact outcomes Genuinely curious, with a strong appetite for continuous learning and improvement We value diversity of experience, perspective, and background and we recognize that how we work is just as important as what we achieve. We’re built around a few consistent ways of working: driving outcomes, innovating, lifting others up, adapting quickly, leading by example, and bringing people together around a shared purpose. We capture these behaviors in six words: Go-Getter, Trailblazer, Elevator, Shapeshifter, Torchbearer, and Steward, and you’ll see them show up in how we collaborate, how we measure performance, and how we get work done day to day. A Go-Getter focuses on what matters most and drives results, with the customer experience in mind; a Trailblazer is curious, proactive, and always looking for better ways to do things; an Elevator lifts others up through listening, collaboration, and crediting contributions; a Shapeshifter stays positive and calm through change and helps others find clarity and momentum; a Torchbearer leads with initiative and accountability, communicating early and acting in the team’s best interests; and a Steward brings steadiness and purpose, uniting people around shared goals with optimism, professionalism, and integrity. ______________________________________________________________________________________________________ About Docuvera Our mission is to help life sciences companies accelerate how to get their life changing products to market faster through digital content management. Instead of treating every document like a giant Word file, Docuvera turns content into reusable, approved building blocks that work safely across documents and markets. They harness the power of this digital innovation, enabling them to raise the bar for safety, quality, and care. Headquartered in New Zealand with a distributed team across New Zealand, Asia, the UK, Europe, and the US, we're now a member of the cormeo family of companies. Why our team love working here As a distributed, global team, we operate a high trust environment and we truly walk the talk. We give our people the tools, flexibility, autonomy, and encouragement they need to thrive. Here’s what that looks like in practice: Work your way. We’re digital-first and fully flexible, with asynchronous work as the norm. Our New Zealand offices in Wellington and Palmerston North are always open; come for the snacks, drinks and amazing city views, stay for the fantastic people and connection. Pride in what we do. There's nothing like joining a tech scale-up that's highly regarded on the world stage where what we do makes a tangible difference in the world. Modern tools that work for you. We use the latest systems and tools to make work smarter. Space to grow. You’ll have access to learning and development resources, plus dedicated tools-down time for personal growth. Time to recharge. In New Zealand, enjoy an extra week of paid leave; time off over Christmas, and your birthday off. In the U.S., we offer unlimited PTO and funded health benefits, including dental and medical. A close-knit global team. You’ll be part of a dedicated, collaborative community that stays connected no matter where you’re based. Keen to know more? Please also feel free to check out the careers page for more information about working with us and follow us on LinkedIn to check out what we've been up to recently. Key information about our recruitment process We use a combination of AI tools and human judgment in areas that are inherently human, like recruitment. We may use AI to support certain stages of the hiring process, such as reviewing applications, analysing resumes, or evaluating responses. These tools help our recruitment team, but they do not replace human interaction or decision making. All final hiring decisions are made by people. If there’s anything we can do to make our recruitment process more inclusive or accessible for you, please let us know. We’re happy to accommodate where we can. Our process usually includes two online interviews, each about an hour long, with one or two members of our team. Some roles may also include a technical exercise to help us understand your approach and skills. We’ll also ask for at least two professional references and usually complete a background and/or verification check. We’ll keep applications open until we find the right person, and we’ll keep you updated along the way. For recruitment agencies: we work with a select group of preferred partners, so please don’t send unsolicited CVs as we won’t be able to consider them. Location New Zealand, Wgtn, Palmy or Remote (Hybrid) Department AI Technology Employment Type Full-time Minimum Experience Experienced

Responsibilities

The Senior Data Engineer will design, build, and operate the enterprise knowledge foundation, focusing on structuring, connecting, and operationalizing enterprise knowledge for AI-enabled products and agentic workflows. This involves building and maintaining an Enterprise Knowledge Graph using semantic standards and operating graph database systems at production scale.