Data Architect

Stack

Responsibilities

• ▹Own the data architecture across OneOcean's data organisation (operational, lakehouse, analytical-serving and vector layers), providing a coherent target state and a pragmatic path to it
• ▹Lead the discovery, documentation and specification of the data structures and models required to support product and analytics roadmaps
• ▹Reverse-engineer source data from OneOcean SaaS products: build accurate logical models of upstream systems and identify the data contracts, grain and semantics the pipelines depend on
• ▹Design the right data store for each use case, choosing between OLTP, columnar/OLAP, lakehouse and vector approaches and making the trade-offs explicit
• ▹Define and maintain conceptual, logical and physical data models; produce clear ERDs, lineage and dimensional designs (star/snowflake, conformed dimensions, surrogate keys)
• ▹Establish and enforce modelling standards, naming conventions, data contracts and schema-evolution practices across teams
• ▹Partner with the Data, BI and AI Team Leads, translating product and analytics needs into specifications their engineers can build from and unblocking architectural decisions
• ▹Collaborate with Product, Architecture and Engineering Team Leads to align data direction with the wider engineering strategy
• ▹Champion data governance: cataloguing, lineage, ownership, quality, security and privacy
• ▹Document architectural decisions (ADRs) so the why is preserved alongside the what
• ▹Mentor engineers across the data organisation on modelling, design and architectural reasoning, without line-managing them
• ▹Stay current with the data landscape, bring in proven techniques as they mature and foster a culture of continuous improvement, innovation and knowledge sharing

Requirements

• ▹8+ years of commercial experience in data engineering, BI engineering or data architecture roles, with significant time spent on modelling and specification
• ▹Demonstrable experience owning data architecture across multiple workloads: operational, analytical, lakehouse and (ideally) AI/vector
• ▹Deep data-modelling expertise: conceptual, logical and physical; dimensional/star-schema; SCD; data contracts; semantic-layer design
• ▹Strong SQL across multiple dialects; comfortable reading and reasoning about complex source-system schemas
• ▹Proven ability to reverse-engineer SaaS/operational systems, discovering grain, primary keys, relationships, soft-delete patterns and quirks that aren't in the docs
• ▹Solid working knowledge of analytical serving (e.g. Apache Druid, Apache Superset, Power BI) and the modelling patterns that make them perform
• ▹Working knowledge of lakehouse approaches (e.g. Delta Lake): MERGE semantics, partitioning, schema evolution
• ▹Pragmatic decision-making: able to balance ideal architecture against delivery pressure and explain the trade-offs clearly
• ▹Excellent written and visual communication: produces specifications and diagrams that engineers can build from with minimal ambiguity
• ▹Exceptional collaboration and stakeholder skills, comfortable bridging engineering, BI, AI, product and business audiences
• ▹Documentation discipline: Confluence-grade architectural records, ADRs, model dictionaries and onboarding material

Nice to have

• ▹Familiarity with vector databases and the modelling considerations for AI/RAG workloads (chunk strategy, metadata schema, embedding versioning)
• ▹Exposure to Data Vault or Anchor modelling alongside dimensional approaches
• ▹Catalog/lineage tooling (e.g. DataHub, Atlan, Collibra or similar) and data-quality frameworks (e.g. Great Expectations, Soda)
• ▹Experience with data contracts as code (e.g. Open Data Contract Standard) or schema registries
• ▹Awareness of relevant data-protection regimes (GDPR, UK GDPR) and how they shape modelling decisions (PII tagging, retention, minimisation)
• ▹Python familiarity sufficient to read pipeline code and collaborate on PRs without needing translation
• ▹Cloud-platform awareness (AWS preferred) and IaC familiarity (Terraform)
• ▹Maritime or other regulated-industry domain experience

Soft skills

About the company

OneOcean is a unified brand born from the integration of OneOcean and Ocean Technologies Group, owned by Lloyd's Register. Its digital solutions are used by more than 30,000 vessels across learning, fleet operations, compliance, voyage planning and performance management.