Data Engineer/ Architect Consultant
Market Cloud
Eschborn 1d ago
Data EngineeringOn-siteMid level
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On-siteMid levelPosted 1d ago
Compensation
Salary & market context
Salary not listed
Requirements
Top requirements
- s
- 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).
Perks & setup
Work setup
- On-site
- Mid level
- Posted 1d ago
Start here
Requirements
- s
- 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).
Responsibilities
What you'll do
- 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.
Role snapshot
About the role
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
Source text
Full listing preview
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
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