Lead Data Architect (Databricks & AI Platforms)

Cognizant; São Paulo; Hybrid; BRL 400,000 - 700,000; Full time

Job summary

Cognizant is seeking a Lead Data Architect (Databricks & AI Platforms) to design and deliver enterprise-scale data platforms, AI-enabled solutions, and modern data products. You will bridge enterprise architecture strategy with engineering execution, ensuring scalable, governed, and business-aligned solutions across large-scale transformation efforts.

The role requires 10+ years in data engineering/architecture, hands-on Databricks Lakehouse experience, and strong PySpark/Python skills.

Qualifications

• 10+ years of experience in Data Engineering, Data Architecture, or Enterprise Data Platforms.
• Hands-on Databricks Lakehouse implementations in enterprise environments.
• Strong SQL, PySpark and Python skills for large-scale ETL/ELT.
• Experience with Data Vault, dimensional modeling, and data governance.

Responsibilities

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

Skills

Data Engineering

Data Architecture

Databricks

PySpark

SQL

Python

ETL/ELT

Data Vault

Governance

CI/CD

Education

Bachelor's degree in Computer Science, Information Technology, Engineering

Tools

Databricks Lakehouse

Delta Lake

Delta Live Tables

Unity Catalog

Databricks SQL

Mosaic AI

Job description

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.

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