Senior Data Engineer (Databricks & AI Solutions)

About the role

As a Senior Data Engineer (Databricks & AI Solutions), you will make an impact by building, operating, and supporting modern data platforms and AI-enabled data engineering solutions. You will work closely with architects, data teams, and business stakeholders to transform requirements into production-ready data products while ensuring data quality, reliability, observability, and operational excellence.

In this role, you will

• Design, develop, and deploy scalable data pipelines using Databricks, PySpark, SQL, and cloud-native technologies.
• Implement and support data quality, lineage, governance, and validation processes across enterprise data products.
• Operate and continuously optimize AI-assisted and agent-based data engineering solutions to improve delivery efficiency and platform performance.
• Lead troubleshooting, root cause analysis, and support activities for data pipelines, platforms, and production incidents.
• Maintain technical documentation, knowledge repositories, and operational runbooks while collaborating with cross-functional teams throughout the data product lifecycle.

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

• 4+ years of hands-on experience in Data Engineering.
• Strong experience with Databricks, Apache Spark, PySpark, SQL, and Python.
• Experience building and maintaining ETL/ELT pipelines in enterprise environments.
• Experience working with cloud platforms, preferably Microsoft Azure.
• Knowledge of Delta Lake, Delta Live Tables, and Unity Catalog.
• Experience implementing data quality, reconciliation, and validation processes.
• Experience with Git-based CI/CD practices for data engineering solutions.
• Exposure to AI-assisted development tools, code generation platforms, or GenAI-enabled engineering workflows.
• Experience supporting production environments, incident management, and root cause analysis.
• Strong analytical, troubleshooting, and problem-solving skills.
• Advanced English proficiency.
• Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field.

These will help you stand out

• Experience with ICEDQ or similar Data Quality frameworks.
• Familiarity with Data Validation Suite (DVS) or automated data testing frameworks.
• Experience with column-level data lineage and data governance initiatives.
• Familiarity with agentic AI platforms and AI-powered data engineering tools.
• Experience with Power BI, Tableau, or other analytics and visualization platforms.
• Knowledge of modern Data Mesh, Data Product, and Data Fabric concepts.
• Azure, Databricks, or cloud-related certifications.
• Experience working in large-scale enterprise data 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.