Data Architect

This is a fully remote position, open to applicants in Romania.

📋 Description

• Take charge of the data architecture within OneOcean's data organization — encompassing operational, lakehouse, analytical-serving, and vector layers — by providing a unified target state and a pragmatic pathway to achieve it.

• Spearhead the discovery, documentation, and specification of the necessary data structures and models to support product and analytics roadmaps.

• Reverse-engineer source data from OneOcean's SaaS products — constructing accurate logical models of upstream systems and identifying the data contracts, granularity, and semantics that our pipelines rely on.

• Create the appropriate data store for each specific use case — selecting from OLTP, columnar/OLAP, lakehouse, and vector approaches; articulating the trade-offs involved.

• Define and uphold conceptual, logical, and physical data models; generate clear ERDs, lineage, and dimensional designs (star/snowflake, conformed dimensions, surrogate keys).

• Set and enforce modeling standards, naming conventions, data contracts, and schema-evolution practices across teams.

• Collaborate with the Data Team Lead, BI Team Lead, and AI Team Lead — translating product and analytics requirements into specifications that engineers can implement, and resolving architectural decisions as they emerge.

• Work alongside Product, Architecture, and Engineering Team Leads to ensure data direction aligns with the broader engineering strategy.

• Advocate for data governance — including cataloging, lineage, ownership, quality, security, and privacy.

• Record architectural decisions (ADRs) to preserve the rationale alongside the outcomes.

• Mentor engineers throughout the data organization on modeling, design, and architectural reasoning — without direct line management.

• Stay updated with the evolving data landscape and integrate proven techniques as they develop; promote a culture of continuous improvement, innovation, and knowledge sharing.

⛳️ Requirements

• Over 8 years of commercial experience in data engineering, BI engineering, or data architecture roles, with a significant focus on modeling and specification.

• Proven experience in owning data architecture across various workloads — operational, analytical, lakehouse, and ideally AI/vector.

• Extensive expertise in data modeling — conceptual, logical, and physical; dimensional/star-schema; slowly changing dimensions (SCD); data contracts; semantic-layer design.

• Proficient in SQL across different dialects; capable of interpreting and reasoning about complex source-system schemas.

• Established ability to reverse-engineer SaaS/operational systems — identifying grain, primary keys, relationships, soft-delete patterns, and nuances not documented.

• Solid understanding of analytical serving (e.g., Apache Druid, Apache Superset, Power BI) and the modeling patterns that enhance their performance.

• Familiarity with lakehouse methodologies (e.g., Delta Lake) — including MERGE semantics, partitioning, and schema evolution.

• Practical decision-making skills — able to balance ideal architecture with delivery pressures and clearly articulate the trade-offs.

• Excellent written and visual communication skills — capable of producing specifications and diagrams that engineers can work from with minimal ambiguity.

• Outstanding collaboration and stakeholder engagement skills — comfortable connecting engineering, BI, AI, product, and business stakeholders.

• Strong documentation discipline — able to maintain Confluence-level architectural records, ADRs, model dictionaries, and onboarding materials.

🏝️ Benefits

• Comprehensive health insurance and wellness programs.

• Opportunities for professional development and continuous learning.

• Flexible work hours and remote work options.

• Engaging and inclusive work environment with a focus on teamwork.

• Competitive salary and performance-based bonuses.