Data Architect Python (ESP/UK)

parser; España; Presencial; EUR 60.000 - 90.000; Jornada completa

Descripción de la vacante

parser is seeking an experienced Data Architect to lead the definition of data architecture for a new data-driven product. This role focuses on assessing, structuring, and integrating fragmented datasets to enable a scalable, decision-support platform for in-house legal teams.

The position combines hands-on data analysis with architectural design, shaping data ingestion, mapping, transformation, and governance to support a viable MVP in an early-stage product environment.

Formación

• Proven experience as a Data Architect or similar role.
• Experience designing scalable data architectures for analytics or decision-support products.
• Strong communication skills bridging technical and product discussions.

Responsabilidades

• Assess data sources, structures, and quality across multiple systems.
• Define data ingestion, mapping, and transformation strategies to unify datasets.
• Design target data architecture to support a scalable MVP (multi-source integration, golden record).
• Collaborate with product, UX, and engineering to ensure architecture supports user needs.

Conocimientos

Data architecture

Data governance

Data modeling

Python

SQL

Communication

Herramientas

AWS

GCP

Azure

Descripción del empleo

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