Data Architect Python (Esp/Uk)

Parser
Málaga, Spain
2 months ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours

Tech stack

Amazon Web Services Data Analysis Microsoft Azure Data Architecture Data Governance Extract Transform Load (ETL) Distributed Systems Python (Programming Language) SQL Databases Data Streaming Cloud Platform System Data Ingestion
+2 more
Data Analytics Data Pipelines

Job description

Job SummaryWe 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 ResponsibilitiesData Architecture & DiscoveryAssess data sources, structures, and quality across multiple systemsDefine data ingestion, mapping, and transformation strategies to unify disparate datasetsDesign 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 feasibilitySystem Design & Technical DefinitionDefine data models, schemas, and integration patterns aligned to product requirementsEstablish approaches for data governance, lineage, and quality managementCollaborate with product, UX, and engineering to ensure architecture supports user needs and workflowsMake pragmatic trade-offs between speed, complexity, and scalability in an MVP contextHands-on Delivery & PrototypingWork directly with datasets to validate assumptions and inform architecture decisionsSupport prototyping of data flows, pipelines, and transformationsContribute to early-stage technical solutions where required (Python, SQL, etc.)Collaboration & Stakeholder EngagementWork closely with stakeholders to understand data ownership, constraints, and prioritiesSupport user research and validation by ensuring data feasibility aligns with product conceptsTranslate complex data challenges into clear, actionable insights for non-technical stakeholdersKey Qualifications / SkillsProven experience as a Data Architect, Senior Data Engineer, or similarStrong experience working with fragmented or multi-source data environmentsAbility to operate in discovery / early-stage product definition, not just implementationExperience designing scalable data architectures for analytics or decision-support productsStrong communication skills, able to bridge technical and product discussionsFamiliarity with data governance, mapping, and data quality challengesTechnical SkillsStrong proficiency in Python and SQLExperience with cloud-based data platforms (AWS, GCP, or Azure)Understanding of data pipeline design, ETL/ELT patterns, and distributed systemsExperience with data modelling, schema design, and integration patternsExposure to modern data architectures (e.g. medallion, event-driven, or similar) is a plus#J-*****-Ljbffr

Requirements

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 #J-*****-Ljbffr

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