Data Architect Python
Parser · Madrid, Community of Madrid, Spain
- Hybrid
- Full-time
- $150,000 / year
- Madrid, Community of Madrid, Spain
Job highlights
- Define data architecture for a new data-driven product.
- Integrate fragmented datasets into a scalable platform.
- Design and prototype data flows, pipelines, and models.
- Collaborate with cross-functional teams on data solutions.
- Ensure data feasibility aligns with product concepts.
About the role
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
Skills & topics
- Data Architect
- Python
- SQL
- Data Engineering
- Data Modeling
- ETL
- ELT
- Cloud Data Platforms
- AWS
- GCP
- Azure
- Distributed Systems
- Data Governance
- Data Quality
- Decision Support Systems
- MVP Development
- Early Stage Product
How to get hired
- Tailor your resume: Highlight experience in data architecture and Python for data-driven products.
- Showcase relevant projects: Detail your work with fragmented datasets and cloud platforms.
- Prepare for technical questions: Be ready to discuss Python, SQL, ETL/ELT, and data modeling.
- Demonstrate collaboration: Emphasize your ability to work with product and engineering teams.
- Understand the product: Research Parser's goals for this data-driven initiative.
Technical preparation
Master Python for data manipulation and scripting.,Practice complex SQL queries for data extraction.,Understand ETL/ELT processes and distributed systems.,Familiarize with cloud data platforms (AWS, GCP, Azure).
Behavioral questions
Describe a time you managed ambiguous data.,How do you balance technical feasibility and product needs?,Explain a complex data challenge to non-technical staff.,How do you approach data governance in new projects?
Frequently asked questions
- What are the primary responsibilities of a Data Architect at Parser?
- As a Data Architect at Parser, you will define and design the data architecture for new data-driven products, focusing on integrating fragmented datasets, establishing data governance, and supporting decision-making platforms. This includes hands-on data analysis, system design, and collaboration with engineering and product teams.
- What technical skills are most important for this Data Architect role at Parser?
- The role requires strong proficiency in Python and SQL. Experience with cloud data platforms (AWS, GCP, Azure), data pipeline design (ETL/ELT), distributed systems, data modeling, and schema design are crucial. Familiarity with modern data architectures is a plus.
- What kind of experience is Parser looking for in a Data Architect candidate?
- Parser seeks candidates with proven experience as a Data Architect or Senior Data Engineer, particularly those with a background in handling fragmented or multi-source data environments. Experience in early-stage product definition and designing scalable data architectures for analytics or decision-support products is highly valued.
- How does this Data Architect role contribute to Parser's goals?
- This Data Architect role is pivotal in building a new, data-driven product. By structuring and integrating key data sources, you will enable a scalable decision-support platform for in-house legal teams, directly impacting product feasibility and success.
- What is the work environment like for a Data Architect at Parser?
- Parser offers an early-stage product environment where you'll balance technical feasibility with product outcomes. You'll operate across ambiguous data landscapes, requiring comfort with discovery and a pragmatic approach to trade-offs between speed, complexity, and scalability.