[Job-32603] Senior Data Developer, Brazil

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.

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