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. 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. Project for a global pharmaceutical company: evolve a continuing education learning pathway library into an engagement platform for healthcare professionals outside field coverage — personalized, orchestrated in real time, and with professional recognition. Personalization depends on reliable data flowing between CRM (Veeva preferred), Data Lake, and Adobe Experience Platform, and on indicators showing whether the professional is returning. 2-year engagement, start planned for November 2026. Position Mission Build and operate the pipelines that feed and drain the data platform: from CRM and Data Lake to AEP and back, with measured quality, LGPD applied, and engagement indicators calculated reproducibly. How the Role is Evaluated Pipelines in production with monitoring, agreed update SLA and error rate. Data quality rules defined and automatically verified (completeness, uniqueness, identity consistency). Activation indicators, 7-day return, and active weeks calculated and reconciled with CJA. No personal data outside legal basis: minimization, pseudonymization, and retention implemented by design. Responsibilities Design and implement ETL/ELT pipelines between CRM (Veeva preferred), Data Lake, and AEP (batch and streaming ingestion; profile, segment, and event export). Model the platform's analytical tables in the Data Lake (Databricks) and calculate engagement and business indicators. Implement data quality: testing, alerting, reconciliation across sources, identity deduplication handling. Apply LGPD to data: classification, pseudonymization, retention and deletion policies, audit trail, fulfilling data subject requests. Support the architect in XDM modeling and identity strategy from the source data perspective. Document pipelines, data dictionary, and lineage; maintain operation runbooks. Sustain pipelines in production and investigate data incidents. Requirements Mandatory: Solid experience in data engineering, with production pipelines. Advanced SQL, Python, and Databricks (Spark, Delta Lake, jobs, and workflows). CRM and Data Lake integration via APIs, connectors, and files; Veeva experience is a strong preference. Data quality: automated testing, monitoring, reconciliation. Metric calculation and governance (definition, versioning, reconciliation with analytics tools). LGPD applied to personal data: minimization, pseudonymization, retention, data subject rights. Native Portuguese and Advanced English for technical documentation. Differentials: AEP experience: ingestion (source connectors, batch and streaming APIs) and export (destinations, Data Landing Zone, Query Service). Databricks or Adobe certifications. Experience in pharmaceutical or healthcare sector. Orchestration (Airflow, Databricks Workflows) and infrastructure as code. Data modeling for personalization and recommendation. #LI-TO1 Project for a global pharmaceutical company: evolve a continuing education learning pathway library into an engagement platform for healthcare professionals outside field coverage — personalized, orchestrated in real time, and with professional recognition. Personalization depends on reliable data flowing between CRM (Veeva preferred), Data Lake, and Adobe Experience Platform, and on indicators showing whether the professional is returning. 2-year engagement, start planned for November 2026. Position Mission Build and operate the pipelines that feed and drain the data platform: from CRM and Data Lake to AEP and back, with measured quality, LGPD applied, and engagement indicators calculated reproducibly. How the Role is Evaluated Pipelines in production with monitoring, agreed update SLA and error rate. Data quality rules defined and automatically verified (completeness, uniqueness, identity consistency). Activation indicators, 7-day return, and active weeks calculated and reconciled with CJA. No personal data outside legal basis: minimization, pseudonymization, and retention implemented by design. Responsibilities Design and implement ETL/ELT pipelines between CRM (Veeva preferred), Data Lake, and AEP (batch and streaming ingestion; profile, segment, and event export). Model the platform's analytical tables in the Data Lake (Databricks) and calculate engagement and business indicators. Implement data quality: testing, alerting, reconciliation across sources, identity deduplication handling. Apply LGPD to data: classification, pseudonymization, retention and deletion policies, audit trail, fulfilling data subject requests. Support the architect in XDM modeling and identity strategy from the source data perspective. Document pipelines, data dictionary, and lineage; maintain operation runbooks. Sustain pipelines in production and investigate data incidents. Requirements Mandatory: Solid experience in data engineering, with production pipelines. Advanced SQL, Python, and Databricks (Spark, Delta Lake, jobs, and workflows). CRM and Data Lake integration via APIs, connectors, and files; Veeva experience is a strong preference. Data quality: automated testing, monitoring, reconciliation. Metric calculation and governance (definition, versioning, reconciliation with analytics tools). LGPD applied to personal data: minimization, pseudonymization, retention, data subject rights. Native Portuguese and Advanced English for technical documentation. Differentials: AEP experience: ingestion (source connectors, batch and streaming APIs) and export (destinations, Data Landing Zone, Query Service). Databricks or Adobe certifications. Experience in pharmaceutical or healthcare sector. Orchestration (Airflow, Databricks Workflows) and infrastructure as code. Data modeling for personalization and recommendation. #LI-TO1 Our benefits: -Health and dental insurance -Meal and food allowance -Childcare assistance -Extended paternity leave -Partnership with gyms and health and wellness professionals via Wellhub (Gympass) TotalPass; -Profit Sharing and Results Participation (PLR); -Life insurance -Continuous learning platform (CI&T University); -Discount club -Free online platform dedicated to physical, mental, and overall well-being -Pregnancy and responsible parenting course -Partnerships with online learning platforms -Language learning platform And many more! More details about our benefits here: https://ciandt.com/br/pt-br/carreiras At CI&T, inclusion starts at the first contact. If you are a person with a disability, it is important to present your assessment during the selection process. See which data needs to be included in the report by clicking here.This way, we can ensure the support and accommodations that you deserve. If you do not yet have the assessment, don't worry: we can support you in obtaining it. We have a dedicated Health and Well-being team, inclusion specialists, and affinity groups who will be with you at every stage. Count on us to make this journey side by side.

[Job-32603] Senior Data Developer, Brazil

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