Data Engineer

- Experience as a Data Engineer or in a similar role
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Bachelor's degree or foreign equivalent in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets

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Do you feel the challenge and the adrenaline kick when a huge data-set stares you in the face and you know that somewhere inside are hidden very important business insights that can fundamentally alter the way top business leaders think and act? Do you enjoy presenting strong data backed insights to business leaders; insights that can topple their long held beliefs and compel them to change their direction completely? If yes, then you are the one we are looking for.
We are looking to invite passionate leaders, with expertise in generate power business insights from very large datasets, on a journey where the primary aim would be to enable needle moving business impacts through statistical analysis. We are looking for leaders who can envision the design and development of analytical infrastructure which can support strategic and tactical decision-making. Those who join this high visibility team would have to navigate through significant ambiguity in defining business problems and converting them to analytical problems.
This role requires additional exposure and experience to Machine Learning.

Key job responsibilities
- Build and maintain data pipelines to ingest and process data from credit bureaus (e.g., Boa Vista, Experian), loan application systems, KYC/AML sources, and repayment/collections platforms, ensuring data freshness and reliability
- Design and optimize the analytical data warehouse (e.g., Redshift, S3-based data lake) to support credit risk modeling, portfolio monitoring, and delinquency tracking (DPD/NPA metrics) at scale
- Support Data Science and Risk teams by building feature engineering pipelines for credit scoring models, underwriting decisioning, and early warning systems for loan defaults
- Implement data quality and reconciliation frameworks
- Develop automated dashboards and reporting infrastructure to surface key lending KPIs — disbursement volumes, approval rates, portfolio-at-risk, collection efficiency — enabling leadership to make data-driven strategic decisions
- Collaborate across Product, Risk, and Compliance teams to translate ambiguous business problems into well-defined data engineering solutions, navigating regulatory constraints around PII handling, data residency, and audit readiness

About the team
Brazil Payments is part of the International Emerging Stores Payments team and focuses on supporting the launch of new payment and financial products to our customers in Brazil.