Data Architect Python

Job Summary

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

Key skills/competency

• Data Architecture
• Python
• SQL
• Data Ingestion
• Data Transformation
• Data Governance
• Cloud Data Platforms
• Data Modeling
• ETL/ELT
• Distributed Systems