Principal Data Architect bei Qualys

Key Responsibilities 

• Architecture: 

• Design and lead the development of a scalable, reliable, compliant and secure data architecture that spans enterprise applications, analytics, reporting needs and guarantees real-time delivery of accurate data 

• Define standards and best practices for data modeling, governance, integrations and managing data lifecycle 

• Develop conceptual, logical, and physical data models to ensure alignment with business requirements 

• Define reusable data integration patterns, data flows, and pipelines across systems, applications, and platforms 

• Strategy and Leadership: 

• Partner with enterprise applications delivery teams and enterprise architecture to ensure our solutions keep data consistent, accurate, and secure 

• Collaborate on the implementation of cloud data platforms (e.g., Snowflake, Redshift, Databricks, Azure Synapse, Big Query) and support the enterprise wide roll out 

• Governance: 

• Monitor and optimize database performance, scalability, and storage strategies. 

• Work with security operations org to ensure compliance with data privacy, security, and regulatory requirements (e.g., GDPR, SOC 2, PCI). 

• Establish governance frameworks ensuring data quality, privacy, lineage, and compliance across all sources.  

• Implement robust data security practices, including RBAC, encryption, and access auditing 

• AI and emerging tech: 

• Infuse AI into the data landscape by setting direction and giving guidance on the development of ML models and other AI based capabilities 

• Enable data democratization and advanced insights through curated datasets, semantic layers, and analytical products 

Qualifications: 

• 15+ years of hands-on experience in the world of data architecture, data warehouses, enterprise-wide analytics, data democratization 

• Strong knowledge of relational and non-relational databases (SQL Server, Oracle, PostgreSQL, MongoDB, Cassandra), data security, and privacy regulations (GDPR, CCPA) 

• Proficiency and prior hands-on experience in cloud-based data platforms (AWS, Azure, GCP, Snowflake, Redshift, Big Query) 

• Strong understanding of APIs, data contracts, and platform-as-a-product concepts. 

• Proven expertise in data modeling (conceptual, logical, physical), data governance, master data management (MDM), data lineage and metadata management. 

• Proven experience in implementing data lakes and data ingestion technologies 

• Prior with BI/reporting tools (Tableau, Power BI, Looker etc.,) 

Communication Skills: 

• Strong analytical and problem-solving skills. 

• Excellent communication skills to work with both technical and business teams. 

• Ability to translate complex technical details into business-friendly terms. 

• Self-starter with the ability to lead cross-functional data initiatives. 

Preferred Certifications (Nice to Have): 

• AWS Certified Data Analytics or Solutions Architect 

• Google Professional Data Engineer 

• Microsoft Azure Data Engineer Associate 

• DAMA Certified Data Management Professional (CDMP) 

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Annual Salary Guidelines: $150,000 - $195,000