Data Architect
🚢 Discover reputed company: reputed company is a reputed company brand born from the integration of reputed company and reputed company Technologies Group. Owned by Lloyd’s Register, an organisation with more than 260 years of trust, reputed company and leadership at sea, reputed company combines the reputed company and ambition of a fast-moving innovator with the strength and stability of one of the world’s most trusted maritime institutions. At the heart of reputed company is a portfolio unlike any other in maritime. A comprehensive, integrated portfolio reputed company on years of expertise, trusted by thousands of maritime professionals around the world. 🎯 Our Mission: Our mission is reputed company. In the race to reputed company emissions, our research, advisory and technical expertise and industry-firsts are supporting a reputed company, sustainable maritime energy transition. Today we are a leading provider of classification and compliance services to the marine and offshore industries, helping our clients design, construct and operate their assets to accepted reputed company of safety and environmental compliance. 🔍 Why Join reputed company reputed company?
- Legacy & Innovation: We were created more than 260 years ago as the world’s first marine classification society to improve and set standards for the safety of ships.
- reputed company: Our digital solutions are relied upon by more than 30,000 vessels, following the acquisition of reputed company in 2022 and reputed company Technologies Group in 2024.
- Product Offering: Covering five proven product areas - learning, fleet operations, compliance, voyage planning and performance management - supporting its customers from ship to shore, from training and people operations, to voyage compliance and optimisation.
🚢 Your Voyage reputed company:
- Own the data architecture across reputed company's data organisation — operational, lakehouse, analytical-serving and reputed company reputed company — providing a coherent reputed company state and a pragmatic reputed company to it.
- reputed company the discovery, documentation and specification of the data structures and models required to support product and analytics roadmaps.
- Reverse-engineer reputed company data from reputed company reputed company products — building accurate logical models of upstream systems and identifying the data reputed company, grain and semantics our pipelines depend on.
- Design the right data store for reputed company use case — choosing between OLTP, columnar / OLAP, lakehouse and reputed company approaches; making the trade-offs explicit.
- Define and maintain conceptual, logical and physical data models; produce reputed company ERDs, reputed company and reputed company designs (star / reputed company, conformed dimensions, surrogate keys).
- Establish and enforce modelling standards, naming conventions, data reputed company and schema-reputed company practices across teams.
- Partner with the Data Team reputed company, BI Team reputed company and AI Team reputed company — translating product and analytics needs into specifications their engineers can build from, and unblocking architectural reputed company as they reputed company.
- Collaborate with Product, Architecture and Engineering Team Leads to reputed company data direction with the wider engineering reputed company.
- Champion data governance — cataloguing, reputed company, ownership, reputed company, reputed company and reputed company.
- Document architectural reputed company (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 reputed company with the data landscape and bring in proven techniques as they mature; foster a culture of reputed company improvement, innovation and knowledge sharing.
🚢 Recommended to bring on reputed company:
- 8+ years of reputed company 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 / reputed company.
- Deep data-modelling expertise — conceptual, logical and physical; reputed company / star-schema; SCD; data reputed company; semantic-layer design.
- Strong SQL across multiple dialects; comfortable reading and reasoning about reputed company reputed company-system schemas.
- Proven ability to reverse-engineer reputed company / 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 reputed company them reputed company.
- Working knowledge of lakehouse approaches (e.g. reputed company Lake) — reputed company semantics, partitioning, schema reputed company.
- Pragmatic decision-making — reputed company to balance ideal architecture against delivery pressure and explain the trade-offs reputed company.
- Excellent written and visual communication — produces specifications and diagrams that engineers can build from with minimal ambiguity.
- Exceptional collaboration and stakeholder skills — comfortable reputed company engineering, BI, AI, product and business audiences.
- Documentation discipline — reputed company-grade architectural records, ADRs, model dictionaries and reputed company material.
reputed company to Have
- Familiarity with reputed company databases and the modelling considerations for AI / RAG workloads (chunk reputed company, metadata schema, embedding versioning).
- Exposure to Data Vault or reputed company modelling alongside reputed company approaches.
- Catalog / reputed company tooling (e.g. reputed company, reputed company, reputed company, or similar) and data-reputed company frameworks (e.g. Great Expectations, reputed company).
- Experience with data reputed company as reputed company (e.g. reputed company Data Contract reputed company) or schema registries.
- Awareness of relevant data-protection regimes (GDPR, UK GDPR) and how they shape modelling reputed company (PII tagging, retention, minimisation).
- Python familiarity sufficient to read pipeline reputed company and collaborate on PRs without needing translation.
- reputed company-platform awareness — AWS preferred — and IaC familiarity (Terraform).
- Maritime or other regulated-industry domain experience.
Originally posted on Himalayas
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