As part of our Engineering Hub in Madrid, we are looking for a Data Architect to lead the design, governance, and evolution of our data ecosystem in a fast-growing video streaming environment. This role combines data architecture, data governance, and applied analytics, with a strong focus on ensuring data quality, consistency, and long-term robustness.
The Data architect will be responsible for defining and implementing the blueprint which will potentially include new frameworks, tools, and processes that guarantee the reliability of data across multiple domains, including:
- Application usage analytics (sessions, views, engagement metrics)
- Content consumption trends (genre, seasonality, time-of-day, geography)
- AI-driven recommendation systems (user behavior-based personalization)
In addition to governance responsibilities, this role requires a hands-on analytical mindset to extract value from data, improve recommendation systems, and enhance customer-centric insights.
This role will work closely with a team of Data Engineers and collaborate with product and client stakeholders to translate business needs into scalable data solutions.
Key Responsibilities:
Data Governance & Quality
- Define and implement a data governance framework ensuring data consistency, reliability, and traceability across systems.
- Establish data validation, regression testing, and monitoring mechanisms to detect anomalies and prevent silent data corruption.
- Design and enforce data contracts and schema evolution strategies between applications and backend systems.
- Introduce data quality metrics, SLAs, and observability tools across the data lifecycle.
- Ensure proper metadata management, lineage tracking, and documentation.
- Cross collaboration with other teams in charge of ingesting data into the system.
Data Architecture
- Design scalable and robust data architectures on Cloud environments, supporting both batch and real-time data pipelines.
- Collaborate with Data Engineers to optimize data ingestion, storage, and querying strategies (e.g., Elasticsearch, data lakes, analytics layers).
- Design and implementation of key value stores mechanisms (e.g. Redis, DynamoDB), SQL (PostgreSQL. MySQL, and Athena S3).
- Use standard data modelling techniques (e.g. Entity Relationships)
- Ensure systems are built for long-term maintainability and evolution.
Analytics & Personalization
- Analyze user behavior data to identify opportunities for improving engagement and retention.
- Contribute to the evolution of recommendation systems, leveraging historical data and user interaction signals.
- Work closely with stakeholders to define and refine KPIs and analytical frameworks.
- Support experimentation and A/B testing initiatives related to content and recommendations.
Stakeholder Collaboration
- Act as a bridge between technical teams and business stakeholders, translating requirements into data solutions.
- Engage in client-facing discussions to understand needs and propose data-driven strategies.
- Drive data literacy and best practices across the organization.
Key Qualifications:
- Proven experience (5+ years) in Data Architecture, Data Engineering, or similar roles.
- Strong background in data governance, data quality, and data modeling.
- Hands-on experience with Python for data processing and analysis.
- Experience with Elasticsearch
- Experience working with AWS ecosystem (e.g., S3, Lambda, etc.).
- Demonstrated skills in database design using entity-relationships
- Solid understanding of data pipeline design and distributed systems.
- Experience working with analytical datasets and user behavior data.
- Previous exposure to data analytics, data science, or recommendation systems.
- Strong understanding of data validation, monitoring, and testing strategies.
- Understanding of SQL (PostgreSQL, MySQL and Athena SQL)
- Understanding of Key Value database using NoSQL (Redis and DynamoDB)
- Understanding of continuous integration and continuous deployment
- Familiar with running databases within a clustered environment.
Desirable Skills:
- Experience in AI usage for development.
- Experience with streaming or media platforms.
- Familiarity with Elasticsearch or similar search/analytics engines.
- Knowledge of ML systems or recommendation algorithms.
- Experience implementing data observability tools
- Experience with Docker and infrastructure-as-code (e.g., CloudFormation).
- Understanding of event-driven architectures and tracking systems.
- Experience with A/B testing frameworks and experimentation platforms.
Personal Attributes:
Strong customer-oriented mindset, with the ability to translate data into business value.
- Excellent communication skills, capable of engaging both technical and non-technical stakeholders.
- Proactive and ownership-driven, with a focus on long-term data reliability.
- Analytical thinker with a problem-solving mindset.
- Comfortable working in cross-functional and collaborative environments.
- Curious and continuously seeking to improve systems, processes, and insights.
