Confirmed on the employer's own hiring board on Oct 30, 2026. First seen by Alion on Oct 29, 2026. CI&T scores A on the Alion truth index.
We are looking for a Data Architect with strong AWS expertise to drive the strategy, development, and execution of our enterprise data platforms and analytics products. In this role, you will bridge the gap between business stakeholders, data engineers, and data science teams to transform raw data assets into scalable, high-value data products. You will leverage cloud-native AWS services to manage the product lifecycle from discovery to rollout, ensuring high data quality, governance, and business impact.
Responsibilities:
- Product Strategy & Roadmap: Define the vision, roadmap, and KPIs for data products (data pipelines, data lakes, analytics dashboards, and AI/ML data features) on AWS.
- Stakeholder Alignment & Discovery: Work with business leaders, domain experts, and engineering teams to identify high-impact use cases, translate business requirements into technical epics, and prioritize the backlogs.
- AWS Data Ecosystem Management: Oversee product architecture alignment on AWS data services (e.g., S3, Glue, Redshift, Athena, Bedrock/SageMaker) to support scalable analytics and GenAI workloads.
- Data Governance & Quality: Partner with Security and Data Governance teams to enforce data access controls, privacy regulations (LGPD/GDPR/HIPAA), data lineage, and data quality standards.
- Execution & Product Delivery: Lead agile development cycles, defining clear acceptance criteria, managing user stories, and ensuring timely delivery of data solutions.
- Adoption & Value Measurement: Track usage metrics, adoption rates, and ROI of data products to continuously optimize user engagement and business value.
Requirements:
- Experience specifically managing data platforms, ETL pipelines, or analytics products.
- AWS Technical Literacy: Solid understanding of the AWS data stack (S3, Redshift, Glue, EMR, Athena, QuickSight, IAM) and cloud-native data architecture patterns (Data Lake, Lakehouse, Data Mesh).
- Agile & Delivery: Strong experience leading cross-functional squads using Scrum/Kanban, backlog management tools (Jira, Linear), and defining clear user stories.
- Data Skills: Proficiency in SQL and data visualization tools, with the ability to query data directly to validate product performance and metrics.
- Business Acumen: Demonstrated track record of converting complex technical requirements into actionable business outcomes and executive-ready communications.
Nice to Have:
- Databricks Certified Consultant (Associate/Professional); DBR to EMR on AWS migration experience
AWS Certified Data Engineer - Associate or AWS Certified Cloud Practitioner
Certified Scrum Product Owner (CSPO) or Pragmatic Institute Certification

