Data Science Specialist – Feature Store & ML Platform

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Spearhead the advancement and enhancement of Feature Store functionalities, including data lineage, feature views, feature recommendations, and the introduction of new query engines;

• Design and execute Apache Iceberg tables with an emphasis on read optimization, version control, and schema evolution;

• Architect and improve the serving layer utilizing Redis for real-time feature delivery with stringent latency service level objectives (SLOs);

• Integrate and optimize Amazon EMR to function as a query and large-scale processing engine;

• Define and implement pipelines for feature selection and transformation, ensuring comprehensive traceability from end to end;

• Set standards for feature quality, version control, and governance throughout the platform;

• Serve as the technical authority for data and data science teams utilizing the Feature Store.

⛳️ Requirements

• Demonstrated expertise in feature engineering on enterprise machine learning platforms such as Feast, Tecton, Hopsworks, or similar;

• Advanced skills in Apache Spark / PySpark for large-scale distributed processing;

• In-depth understanding of Apache Iceberg and lakehouse architectures, with comparative knowledge of Delta Lake and Hudi;

• Proficiency in Redis for low-latency feature serving, including strategies for cache invalidation and efficient serialization;

• Substantial production experience with AWS data services including S3, Glue, EMR, Redshift, and Athena;

• Preferred qualifications include:

• Experience in production environments involving data lineage and metadata catalogs (such as DataHub, OpenMetadata, Marquez);

• Familiarity with Amazon EMR, including cluster configuration, optimization, and Spark job tuning;

• Expertise in MLOps practices focused on the versioning and traceability of data artifacts;

• Previous experience within a financial context, dealing with high-cardinality, high-frequency data and regulatory demands;

• Knowledge of data quality tools at scale, such as Great Expectations, Soda, or dbt tests.

🏝️ Benefits

• Competitive salary and performance-based bonuses;

• Comprehensive health, dental, and vision insurance;

• Flexible working hours and remote work options;

• Opportunities for professional development and career advancement;

• Collaborative and innovative work environment.