The posting
About Zinkworks
Zinkworks partners with leading Telecommunications and Financial Services organizations to modernize legacy systems, migrate mission-critical platforms to the cloud, and engineer AI-driven automation. From OSS transformation to rApp development and network intelligence, our teams simplify complexity and turn it into competitive advantage. Based in Ireland and operating across the EU, UK, and US, Zinkworks combines deep domain expertise with delivery excellence to help clients modernize faster and operate smarter.
About the Role
We're looking for an experienced Data Modeller who enjoys uncovering how data really works within complex enterprise systems.
A key part of this role involves analysing existing source systems, understanding their data models, and mapping how information flows across platforms. Using SQL, data profiling techniques, and occasionally Python, you'll investigate datasets, discover relationships, document business entities, and build a detailed understanding of the underlying data landscape.
You'll use these insights to design target data models that bring together data from multiple source systems into a coherent structure that supports software solutions, reporting, analytics, and AI-driven capabilities.
A key aspect of the role is ensuring that target models are not only functionally correct but also performant. You'll need to understand how modelling decisions impact query performance, scalability, data ingestion patterns, and application behaviour across graph-database and relational database platforms.
This is a modelling and analysis-focused role rather than a traditional data engineering role. Success comes from understanding complex business domains, discovering how data is organised, and translating that understanding into robust, scalable solution-focused data designs.
What You'll Do
- Analyse source systems to understand existing data structures, relationships, data quality, and business meaning.
- Use SQL and data profiling techniques to investigate datasets, validate assumptions, and uncover hidden dependencies.
- Reverse engineer and document existing data models where formal documentation is incomplete or unavailable.
- Collaborate with business stakeholders and subject matter experts to understand how data is created, maintained, and consumed.
- Identify common business entities and relationships across multiple source systems.
- Design conceptual, logical, and physical target data models that consolidate and harmonise data from disparate source systems.
- Design graph database models that accurately represent complex relationships and support efficient traversal and query patterns.
- Define source-to-target mappings and transformation requirements.
- Evaluate modelling decisions against performance, scalability, and operational requirements.
- Create and maintain data dictionaries, business glossaries, entity definitions, and modelling documentation.
- Assess the impact of source-system changes on downstream systems and target models.
- Work closely with architects and engineering teams to ensure models are implemented consistently and accurately.
- Champion best practices in data modelling, governance, metadata management, and data quality.
Essential Skills & Experience
- Experience creating and implementing target graph database models using technologies such as Neo4j, Spanner Graph, Gremlin, or similar graph platforms.
- Proven experience analysing and modelling complex enterprise data landscapes.
- Strong SQL skills with the ability to query, profile, explore, and validate large datasets.
- Experience investigating existing source systems and developing an understanding of undocumented or poorly documented data structures.
- Strong conceptual, logical, and physical data modelling skills.
- Proven experience designing target data models that integrate data from multiple source systems.
- Proven experience designing optimised relational data models.
- Strong understanding of graph modelling concepts, including nodes, relationships, traversal patterns, and performance considerations.
- Understanding of how data model design affects system performance, scalability, query efficiency, and application behaviour.
- Experience balancing business requirements with performance and operational constraints when designing target models.
- Experience working with cloud platforms such as Azure, AWS, or GCP.
- Ability to identify and model business entities, relationships, hierarchies, and business rules.
- Experience producing source-to-target mappings and transformation specifications.
- Strong analytical and problem-solving skills.
- Excellent stakeholder engagement and communication skills.
Desirable Skills & Experience
- Experience with Google Cloud Platform (GCP), particularly BigQuery, Cloud Spanner, and Spanner Graph.
- Telecoms domain experience, particularly OSS/BSS, network inventory, or service assurance platforms.
- Experience with Master Data Management (MDM) and reference data management.
- Familiarity with metadata management, lineage, and data cataloguing tools.
- Experience supporting data models for AI, knowledge graph, or machine learning solutions.
- Python for data exploration, profiling, reconciliation, and data quality analysis.
At Zinkworks, we are deeply committed to fostering a culture of diversity, inclusion, and belonging. We believe that our strength lies in the unique backgrounds, perspectives, and experiences of our team members. By embracing an inclusive environment, we empower innovation and collaboration across all levels of our organisation. Based in Ireland, we are proud to support and engage with our local communities through meaningful initiatives that promote equity and opportunity. Our commitment extends beyond the workplace, as we actively contribute to creating a more inclusive and connected society for all.
