[Job-32426] Data Architect (Databricks), Brazil
Summary
Data Architect (Databricks) shaping and delivering enterprise data platforms and analytics products on AWS for CI&T clients — defining roadmaps and KPIs, aligning business and engineering stakeholders, enforcing data governance (LGPD/GDPR/HIPAA), and leading agile squads. Core stack: AWS data services (S3, Redshift, Glue, EMR, Athena, SageMaker/Bedrock), SQL, and Databricks.
At CI&T, we help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions.
With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data & AI, Martech and Business strategy.
We are 8,000 CI&Ters across more than 25 countries, collaborating to build solutions with real impact. AI is already part of how we work, evolve, and innovate every day.
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.
- Databricks Certified Consultant (Associate/Professional); DBR to EMR on AWS migration experience
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AWS Certified Data Engineer – Associate or AWS Certified Cloud Practitioner
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Certified Scrum Product Owner (CSPO) or Pragmatic Institute Certification
Skills
- Acceptance Criteria
- Agentic AI
- Agile
- AI
- Analytics
- Athena
- AWS
- Cloud
- Cloud Native
- Data Governance
- Data Lake
- Data Lineage
- Data Mesh
- Data Pipelines
- Data Quality
- Data Science
- Data Visualization
- Databricks
- ETL
- Gdpr
- Generative AI
- Hipaa
- IAM
- Jira
- Kanban
- Lakehouse
- Lgpd
- Machine Learning
- Redshift
- S3
- SageMaker
- Scrum
- SDLC
- SQL
- User Stories
As published by lever · 20 questions
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