Lead Data Architect (Databricks & AI Platforms)

About the role

As a Lead Data Architect (Databricks & AI Platforms), you will make an impact by designing and delivering enterprise-scale data platforms, AI-enabled solutions, and modern data products. You will serve as the technical bridge between enterprise architecture strategy and engineering execution, ensuring scalable, governed, and business-aligned solutions while driving measurable outcomes across large-scale transformation initiatives.

In this role, you will

• Design and lead the implementation of enterprise data architectures, including Data Products, Data Vault models, ETL/ELT pipelines, and Databricks Lakehouse solutions.
• Drive the integration of GenAI and AI-powered engineering capabilities into modern data platforms to improve automation, productivity, and operational efficiency.
• Own the technical delivery of strategic roadmap initiatives, ensuring alignment with business objectives, KPIs, and platform governance standards.
• Establish best practices for data quality, lineage, governance, observability, and lifecycle management across enterprise data assets.
• Lead and mentor engineering teams, providing architectural guidance, technical reviews, and support for complex technical challenges.

Work Model

Hybrid | São Paulo, Brazil

This role follows Cognizant's hybrid work model, requiring periodic onsite collaboration while supporting global teams and stakeholders.

What you need to have to be considered

• 10+ years of experience in Data Engineering, Data Architecture, or Enterprise Data Platforms.
• Proven experience leading large-scale data transformation and modernization initiatives.
• Hands-on experience implementing Databricks Lakehouse solutions in enterprise environments.
• Strong expertise with Databricks, including Delta Lake, Delta Live Tables (DLT), Unity Catalog, Databricks SQL, and Mosaic AI.
• Advanced experience with PySpark, SQL, Python, and large-scale ETL/ELT frameworks.
• Strong knowledge of Data Vault, dimensional modeling, canonical data models, and Source-to-Target Mapping (STTM).
• Experience integrating AI/GenAI capabilities into production-grade data platforms.
• Experience designing and implementing data governance, lineage, observability, and data quality frameworks.
• Experience with CI/CD, automated testing, and deployment pipelines for enterprise data solutions.
• Strong stakeholder management, leadership, and communication skills.
• Advanced English proficiency.
• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.

These will help you stand out

• Experience with ERP modernization or large-scale migration programs, including SAP S/4HANA, Teradata modernization, or cloud migrations.
• Experience with ICEDQ, Great Expectations, DLT Expectations, or similar data quality frameworks.
• Knowledge of Data Mesh, Data Fabric, and Data Product operating models.
• Experience with AI-powered platform services, agentic AI solutions, and intelligent automation frameworks.
• Familiarity with Power BI, Tableau, Qlik Sense, and modern analytics platforms.
• Understanding of FinOps, cloud cost optimization, and platform governance practices.
• Databricks, Azure, AWS, Google Cloud, or Enterprise Architecture certifications.
• Experience leading global engineering teams and enterprise-scale transformation programs.

Please upload your resume in English

Please upload your resume in English. Resumes will be reviewed by global stakeholders involved in the selection process.

We're excited to meet people who share our mission.