Brazil
GFT Technologies SE
Experian
Analytics Engineer (Pleno)
Brazil
São Paulo, São Paulo, Brazil
PythonSQLAWSKubernetes
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Company Description
Serasa Experian is the first and largest Datatech in Brazil. A leader in intelligence solutions for risk and opportunity analysis, focusing on credit, authentication, and fraud prevention journeys. With cutting-edge technology, innovation, and the best talent, it transforms risk uncertainty into the best decision, helping people achieve their dreams and companies of all sizes and segments to thrive.
We have 22.000 people operating in 32 countries and every day we are investing in new technologies, talented professionals, and innovation to help all clients maximize every opportunity. With corporate headquarters in Dublin, Ireland, Experian is listed on the London Stock Exchange (EXPN) and is part of the FTSE 100 index.
Additional Information
Serasa Experian is much more than you imagine. With the purpose of creating a better future, expanding opportunities for people and companies, in Brazil we are over 4 thousand people working in various teams and specialties. Here, every knowledge and diversity complements each other, and you can work in what you love most. We are committed to building an inclusive culture and an environment where people can balance their careers with their personal commitments and interests, prioritizing well-being.
We are dedicated to being one of the best and most innovative companies to work for in the country, enabling incredible experiences and careers for our people. Our strong people-first approach is externally recognized through various market certifications: we have been awarded by Great Place To Work™ in 24 countries and by the international Top Employers certification, in addition to being recognized as one of the best companies for young professionals and having a 4,6 rating on Glassdoor. Each recognition indicates that we are on the right path, providing an ever-improving work environment for our talent.
Experian Careers - Creating a better tomorrow together
Job Description
Job description
Find out what its like to work for Experian by clicking here
Employee Status: Regular
Role Type: Home
Department: Technology
Schedule: Full Time
- Build, evolve, and maintain data products and features that support statistical models and analytical applications, translating raw data into reliable and reusable assets.
- Develop and maintain scalable data pipelines (batch and/or streaming), ensuring efficiency, reliability, and data quality throughout the entire cycle.
- Act in the modeling of analytical data (e.g., bronze, silver, and gold layers), ensuring clarity, performance, and reusability of structures.
- Ensure governance, quality, and observability of data products and features (tests, monitoring, SLAs, and alerts).
- Perform and evolve data movement processes (syncs) between analytical and production environments, ensuring consistency and traceability.
- Work in partnership with Product, Engineering, Infrastructure, Security, and Governance teams, acting as a bridge between technical and business areas.
- Propose continuous improvements in data platforms, pipelines, and architecture.
- Develop reports and dashboards when necessary, focusing on enabling product and technology decisions.
- Ensure clear documentation and standardization of processes, datasets, and features.
Qualifications
- Proficiency in SQL and Python for data transformation and analysis.
- Experience with distributed processing (Spark) and platforms like Databricks.
- Experience in building and maintaining data pipelines (Airflow or similar).
- Experience with code versioning (Git) and software engineering best practices.
- Knowledge of CI/CD applied to data pipelines.
- Experience in analytical data modeling (dimensional, data marts, bronze/silver/gold layers).
- Experience with data testing and quality (data quality, validation, monitoring).
- Knowledge of cloud environments and data services (AWS, Azure, or equivalents).
- Clear communication skills with diverse audiences (technical and business).
Qualifications
SQL and Spark
Python
Airflow, Databricks
CI/CD, Git, Data Pipelines
Cloud (Azure, AWS)
Data Quality, Monitoring, Governance
Preferred Qualifications
- Experience with feature platforms / feature store.
- Knowledge of Data Contracts and modern data governance.
- Experience with Kubernetes or distributed architecture.
- Experience with DataOps and/or data observability.
- Familiarity with statistical model concepts and machine learning.
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