1 month ago
São Paulo, BrazilMid Level
Responsibilities
- Design and build CRM data solutions including datasets, tables, business rules, and pipelines for campaigns, customer journeys, and relationship strategies.
- Develop scalable, automated, reusable customer segmentations and customer intelligence solutions.
- Evolve CRM data architecture through modeling, integration, performance optimization, data quality, observability, and governance.
- Develop and productionize reliable data products and services for CRM and other company teams.
- Build solutions with SQL, Python, and Databricks focused on automation, efficiency, scalability, and reduced manual work.
- Apply AI Engineering and GenAI concepts to build automations, agents, tools, and solutions that improve access to data, insights, and knowledge.
- Create data democratization mechanisms that increase business-team autonomy and reduce dependence on manual analysis.
- Work with stakeholders to translate business problems into technical requirements, data solutions, and measurable hypotheses.
- Develop proofs of value, experiments, and measurement mechanisms to evaluate solution impact.
- Maintain documentation, versioning, testing, monitoring, and ongoing maintenance of developed solutions.
- Own delivery planning, estimation, scope and deadline negotiation, risk identification, and progress reporting.
Requirements
- Advanced SQL experience, including manipulation and transformation of large data volumes.
- Experience developing and operationalizing data solutions with Databricks.
- Python experience applied to engineering, automation, data processing, and data analysis.
- Knowledge of data engineering, including pipelines, ETL/ELT, modeling, integration, and data quality.
- Knowledge of AI Engineering and GenAI, including building and integrating LLM-based solutions, automations, and agents.
- Ability to develop production-oriented solutions designed for scalability, reliability, and reuse rather than one-off analyses.
- Ability to connect technical decisions to business objectives and outcomes.
- Clear communication and ability to work with both technical and business stakeholders.
- Autonomy, organization, estimation skills, and ability to manage personal deliveries.
- Experience with CRM, Customer Analytics, customer segmentation and activation, experimentation or A/B testing, APIs, Git, Lakehouse architecture, Delta Lake, MLflow, and AI solutions integrated into corporate environments is a differentiator.
Categories
AI ApplicationsData Engineering
About Experian
Experian builds credit reporting, identity and fraud prevention, and data analytics software that help lenders, insurers, healthcare providers, and marketers make decisions; it also offers consumer credit monitoring and scores. The company earns via data licensing, decisioning software, and subscription services, operates in 30+ countries, is headquartered in Costa Mesa, California, and is a FTSE 100 public company listed on the London Stock Exchange (EXPN); it is one of the three major U.S. credit bureaus.