8 months ago
Responsibilities
- Own and evolve scalable, reliable data pipelines and datasets supporting analytics, reporting, and machine learning.
- Build and maintain ETL/ELT pipelines ingesting data from transactional systems, third-party providers, and event streams into data warehouses and feature stores.
- Partner with analytics and business stakeholders to model, document, and enable self-service access to data.
- Build feature pipelines and feature stores supporting model training, validation, and online/offline inference.
- Implement data quality checks, monitoring, alerting, and service-level agreements for data products.
- Build tooling, abstractions, and CI/CD pipelines to improve the development, testing, and deployment of data pipelines.
- Collaborate with Software Engineering, ML Engineering, Product, Analytics, Marketing, and Risk teams on data models and pipelines.
- Improve the performance, cost efficiency, reliability, and scalability of the data infrastructure.
Requirements
- At least 5 years of experience in data engineering, software engineering, or backend engineering with significant ownership of production data systems.
- Strong proficiency in Python for data pipelines and infrastructure.
- Advanced SQL skills and deep experience with data modeling for analytics and machine learning use cases.
- Hands-on experience building ETL/ELT pipelines with Airflow, AWS Glue, dbt, or similar orchestration systems.
- Experience with cloud data warehouses and query engines such as Athena/Presto, Redshift, BigQuery, or Snowflake.
- Familiarity with Spark or an equivalent big data or distributed processing framework.
- Experience designing and maintaining CI/CD pipelines for data workflows.
- Experience with AWS or similar cloud ecosystems, including services such as S3, IAM, Lambda, Glue, and EMR.
- Strong understanding of data reliability, observability, and production-system best practices.
- Ability to write clean, maintainable, and well-tested code.
- Proven ability to collaborate cross-functionally with Analytics, ML, and Product teams.
- Strong communication skills for explaining technical concepts and aligning on trade-offs.
- Exposure to feature stores, ML data pipelines, or collaboration with ML Engineering teams is preferred.
Benefits
- Very competitive salary and equity are offered, with no specific salary amount stated.
- 100% medical, dental, and vision insurance coverage is provided for the employee.
- Unlimited PTO is provided.
- A 401(k) is available for US-based employees.
- Extended maternity and paternity leave are provided.
- Relocation support is available.
- The role is in-office in Mexico City or New York City.
Tech Stack
Categories
Data Engineering
About Nelo
Nelo builds a consumer credit and payments platform for shoppers in Mexico, offering an app and merchant checkout that function as a modern alternative to credit cards. The company earns revenue from consumer lending and transaction fees to participating merchants. Founded in 2019 and headquartered in Mexico City, it has offices in New York and is backed by investors including Homebrew, Two Sigma Ventures, Susa Ventures, and a credit facility from Victory Park Capital.