The Role
Lead design and delivery of scalable, secure Snowflake-based data platforms. Define architecture standards, build DBT ETL/ELT pipelines, enforce governance, ensure GDPR and pharma compliance, implement CI/CD/DataOps, optimize performance, mentor teams, and collaborate with global stakeholders for analytics and clinical insights.
Summary Generated by Built In
Must have skills: Data Engineering/Architect with Snowflake, AWS, dbt, Python and SQL, Data Mesh.
Seeking a highly experienced Tech Lead / Senior Architect – Data Engineering to drive the design and implementation of enterprise-grade data platforms for a global engagement. This role will focus on building scalable, secure, and compliant data solutions to support advanced analytics, clinical insights, and business intelligence.
Tasks
Key Responsibilities
Lead the end-to-end architecture, design, and implementation of scalable data platforms using Snowflake.
Define and enforce data architecture standards, including modeling, naming conventions, and best practices.
Design and implement robust ETL/ELT pipelines using DBT and cloud-native tools.
Collaborate with global stakeholders (business, analytics, clinical, and IT teams) to translate requirements into scalable solutions.
Drive data governance, lineage, cataloging, and quality frameworks across the platform.
Ensure compliance with European data regulations (e.g., GDPR) and pharma-specific standards.
Implement CI/CD pipelines and DataOps practices for automated testing, deployment, and monitoring of data workflows.
Optimize Snowflake performance, including query tuning, clustering, and cost management.
Provide technical leadership, architectural guidance, and mentorship to engineering teams.
Evaluate emerging tools and technologies to continuously improve the data ecosystem.
Work closely with DevOps and infrastructure teams to ensure high availability, scalability, and security.
Requirements
Mandatory Skills
Strong hands-on expertise in Snowflake (data warehousing, performance tuning, security, cost optimization).
Deep understanding of data warehousing concepts (dimensional modeling, star/snowflake schemas).
Advanced proficiency in SQL and complex query optimization.
Extensive experience in ETL/ELT development, especially with DBT.
Experience in data architecture and distributed data systems design.
Strong exposure to CI/CD pipelines (Git, Jenkins, GitHub Actions, Azure DevOps).
Experience working with cloud platforms (AWS).
Preferred Skills
Experience with orchestration tools like Apache Airflow or similar.
Exposure to data lake / lakehouse architectures.
Experience with data visualization tools (Tableau, Power BI).
Prior experience in pharmaceutical / healthcare domain (clinical, R&D, or commercial data).
Leadership & Soft Skills
Strong stakeholder management and communication skills across business and technical teams.
Ability to drive architecture decisions and influence enterprise data strategy.
Experience working in Agile/Scrum environments
Seeking a highly experienced Tech Lead / Senior Architect – Data Engineering to drive the design and implementation of enterprise-grade data platforms for a global engagement. This role will focus on building scalable, secure, and compliant data solutions to support advanced analytics, clinical insights, and business intelligence.
Tasks
Key Responsibilities
Lead the end-to-end architecture, design, and implementation of scalable data platforms using Snowflake.
Define and enforce data architecture standards, including modeling, naming conventions, and best practices.
Design and implement robust ETL/ELT pipelines using DBT and cloud-native tools.
Collaborate with global stakeholders (business, analytics, clinical, and IT teams) to translate requirements into scalable solutions.
Drive data governance, lineage, cataloging, and quality frameworks across the platform.
Ensure compliance with European data regulations (e.g., GDPR) and pharma-specific standards.
Implement CI/CD pipelines and DataOps practices for automated testing, deployment, and monitoring of data workflows.
Optimize Snowflake performance, including query tuning, clustering, and cost management.
Provide technical leadership, architectural guidance, and mentorship to engineering teams.
Evaluate emerging tools and technologies to continuously improve the data ecosystem.
Work closely with DevOps and infrastructure teams to ensure high availability, scalability, and security.
Requirements
Mandatory Skills
Strong hands-on expertise in Snowflake (data warehousing, performance tuning, security, cost optimization).
Deep understanding of data warehousing concepts (dimensional modeling, star/snowflake schemas).
Advanced proficiency in SQL and complex query optimization.
Extensive experience in ETL/ELT development, especially with DBT.
Experience in data architecture and distributed data systems design.
Strong exposure to CI/CD pipelines (Git, Jenkins, GitHub Actions, Azure DevOps).
Experience working with cloud platforms (AWS).
Preferred Skills
Experience with orchestration tools like Apache Airflow or similar.
Exposure to data lake / lakehouse architectures.
Experience with data visualization tools (Tableau, Power BI).
Prior experience in pharmaceutical / healthcare domain (clinical, R&D, or commercial data).
Leadership & Soft Skills
Strong stakeholder management and communication skills across business and technical teams.
Ability to drive architecture decisions and influence enterprise data strategy.
Experience working in Agile/Scrum environments
Skills Required
- Hands-on expertise in Snowflake (warehousing, tuning, security, cost optimization)
- Deep understanding of data warehousing concepts (dimensional modeling, star/snowflake schemas)
- Advanced proficiency in SQL and complex query optimization
- Extensive ETL/ELT development experience, especially with dbt
- Experience in data architecture and distributed data systems design
- Hands-on experience with cloud platforms (AWS)
- Strong exposure to CI/CD pipelines and tools (Git, Jenkins, GitHub Actions, Azure DevOps)
- Proficiency in Python for data engineering tasks
- Familiarity with Data Mesh principles and implementations
- Experience with orchestration tools like Apache Airflow
- Exposure to data lake / lakehouse architectures
- Experience with data visualization tools (Tableau, Power BI)
- Prior experience in pharmaceutical / healthcare domain (clinical, R&D, commercial data)
- Experience working in Agile/Scrum environments and stakeholder management
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The Company
What We Do
Market Cloud Ltd is a specialized IT services and consulting firm that helps companies transform digital potential into business reality. They specialize in solution architecture, enterprise consulting, data analytics, and artificial intelligence, delivering solutions using technologies like SAP S/4 HANA, Azure, AWS, and GCP. Their mission is to help businesses become more innovative and agile while improving IT resilience at a lower total cost of ownership.
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