We are looking for an experienced Data Architect to lead the definition of data architecture for a new, data-driven product. This role will focus on assessing, structuring, and integrating fragmented datasets (rankings, submissions, engagement data) to enable a scalable, decision-support platform for in-house legal teams.
The role combines hands-on data analysis with architectural design, shaping how data is ingested, mapped, transformed, and governed to support a viable MVP. The ideal candidate will be comfortable working in early-stage product environments, balancing technical feasibility with product outcomes, and operating across ambiguous data landscapes.
Key Responsibilities
Data Architecture & Discovery
- Assess data sources, structures, and quality across multiple systems
- Define data ingestion, mapping, and transformation strategies to unify disparate datasets
- Design target data architecture to support a scalable MVP (e.g. multi-source integration, golden record approach)
- Identify gaps, risks, and constraints in current data that impact product feasibility
System Design & Technical Definition
- Define data models, schemas, and integration patterns aligned to product requirements
- Establish approaches for data governance, lineage, and quality management
- Collaborate with product, UX, and engineering to ensure architecture supports user needs and workflows
- Make pragmatic trade-offs between speed, complexity, and scalability in an MVP context
Hands-on Delivery & Prototyping
- Work directly with datasets to validate assumptions and inform architecture decisions
- Support prototyping of data flows, pipelines, and transformations
- Contribute to early-stage technical solutions where required (Python, SQL, etc.)
Collaboration & Stakeholder Engagement
- Work closely with stakeholders to understand data ownership, constraints, and priorities
- Support user research and validation by ensuring data feasibility aligns with product concepts
- Translate complex data challenges into clear, actionable insights for non-technical stakeholders
Key Qualifications / Skills
- Proven experience as a Data Architect, Senior Data Engineer, or similar
- Strong experience working with fragmented or multi-source data environments
- Ability to operate in discovery / early-stage product definition, not just implementation
- Experience designing scalable data architectures for analytics or decision-support products
- Strong communication skills, able to bridge technical and product discussions
- Familiarity with data governance, mapping, and data quality challenges
Technical Skills
- Strong proficiency in Python and SQL
- Experience with cloud-based data platforms (AWS, GCP, or Azure)
- Understanding of data pipeline design, ETL/ELT patterns, and distributed systems
- Experience with data modelling, schema design, and integration patterns
- Exposure to modern data architectures (e.g. medallion, event-driven, or similar) is a plus
