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Key Responsibilities

Information & Data Architecture

 Define and maintain enterprise and solution-level information architecture for healthcare data platforms.

 Translate business and analytical requirements into logical, conceptual, and physical data models.

 Design scalable data structures, data domains, data products, and integration patterns.

 Define data flows across source systems, cloud platforms, analytical layers, and downstream consumers.

 Establish architecture standards for data ingestion, transformation, storage, consumption, and lifecycle management.

 Support the development of reusable and scalable data architecture patterns.

Snowflake & Data Platform Architecture:

 Design and implement scalable data architectures using Snowflake.

 Define Snowflake database, schema, warehouse, role, and data-sharing strategies.

 Design solutions for structured and semi-structured healthcare data.

 Optimize data models and workloads for performance, scalability, and cost.

 Establish appropriate patterns for data security, access control, data retention, and environment management.

Dbt & Data Transformation:

 Define transformation architecture and development standards using dbt.

 Develop and review dbt models, macros, tests, documentation, and dependencies.

 Establish reusable transformation patterns and data quality frameworks.

 Implement data lineage and documentation across transformation pipelines.

 Collaborate with engineering teams to promote modular, maintainable, and testable data pipelines.

SQL & Python:

 Develop and review complex SQL queries, data transformations, stored procedures, and analytical data models.

 Use Python for data processing, automation, validation, orchestration, and integration requirements.

 Perform data profiling, analysis, reconciliation, and root-cause analysis.

 Develop utilities and frameworks to improve data engineering and operational efficiency.





AWS Cloud Architecture:

 Design and integrate data solutions across AWS cloud services.

 Work with services such as S3, RDS, Redshift, Lambda, IAM, Glue, CloudWatch, and related AWS data services as appropriate.

 Define secure and scalable data movement and integration patterns between AWS and Snowflake.

 Apply cloud architecture best practices for availability, security, scalability, and cost optimization.

CI/CD & DevOps:

 Define and implement CI/CD practices for data engineering and architecture components.

 Integrate Git-based source control, automated testing, deployment pipelines, and environment promotion into the data platform lifecycle.

 Establish automated quality gates for SQL, dbt, Python, infrastructure, and data pipeline changes.

 Collaborate with DevOps/platform teams on deployment automation and Infrastructure as Code.

 Support controlled promotion across development, test, UAT, and production environments.

Document Intelligence & Intelligent Data Extraction:

 Design and implement Document Intelligence solutions to extract, classify, process, and enrich structured and unstructured documents.

 Build scalable pipelines using Snowflake Cortex, GenAI, AWS, and dbt to convert document content into analytics-ready data.

 Experience with OCR, document parsing, information extraction, summarization, entity extraction, and metadata generation.

 Implement data-quality, validation, security, governance, and compliance controls for sensitive healthcare documents.





 Optimize document-processing solutions for accuracy, scalability, performance, and cost.

 Collaborate with architecture, data science, AI/ML, and business teams to deliver document-driven use cases

Required Skills & Experience:

 Experience in data architecture, information architecture, data engineering, or related technology roles.

 Strong hands-on experience with Snowflake.

 Strong experience with dbt and modern ELT/data transformation architectures.

 Advanced SQL skills.

 Strong Python programming experience.

 Hands-on experience with AWS cloud and data services.

 Strong understanding of data modeling, data warehousing, data lakes/lakehouses, and modern data platforms.

 Experience designing enterprise-scale data pipelines and integration architectures.

 Strong understanding of CI/CD, Git, automated testing, and DevOps practices.

 Experience working with data governance, metadata, lineage, data quality, security, and access-control frameworks.

 Experience producing architecture documentation and communicating technical concepts to diverse stakeholders.

Preferred Skills:

 Experience with Snowflake security features including RBAC, masking, row-level access, and secure data sharing.

 Experience with dbt testing, documentation, snapshots, incremental models, and lineage.

 Experience with GitHub Actions, Jenkins, or similar CI/CD platforms.

 Experience with data catalog, metadata management, and data governance tools.

 Knowledge of APIs, event-driven architectures, and cloud-based integration patterns.

Key Competencies

 Enterprise Data Architecture / Information Architecture

 Snowflake Architecture

 Data Modeling

 dbt / ELT Architecture

 SQL & Python

 AWS Cloud Architecture

 Data Integration

 Data Governance & Data Quality

 CI/CD & DevOps

 Document Intelligence

📌 Data Architect (Barcelona)
🏢 Virtusa Europe
📍 Barcelona