Senior Data Engineer - Credit Reporting Pipelines (Remote)

Sezzle; México; Presencial; MXN 946.000 - 1.261.000; Jornada completa

Descripción de la vacante

Sezzle is seeking a Senior Data Engineer in Mexico to own data pipelines, transformations, and reporting that furnish customer account information to credit bureaus. You will work in a fast-growing team, debugging SQL and Python workflows, partnering with Customer Service, Compliance, and Engineering to resolve issues and deliver reliable reporting.

You will lead data-driven improvements, implement automated tests, and ensure data quality across the credit reporting stack while leveraging AI

Formación

• Bachelor's degree in computer science, engineering, data science, or a related quantitative discipline.
• 5+ years of relevant experience in data engineering or software engineering, including hands‑on ownership of production data pipelines and operational workflows.
• Advanced SQL skills, including complex joins, account‑level reconciliation, data profiling, and troubleshooting transformation logic.
• Strong Python skills, including the ability to read unfamiliar code, debug existing scripts, and implement maintainable fixes.
• Demonstrated ability to independently investigate ambiguous problems, prioritize recurring operations and incidents, and carry issues through to verified resolution.
• Experience with version control, code review, automated testing, monitoring, and safe deployment and reprocessing of data workflows.
• Excellent problem‑solving skills, with a track record of tracing data defects across systems and preventing recurrence.
• Strong business judgment and communication skills; able to explain technical findings to Customer Service and Compliance and work effectively with Engineering.
• Demonstrated experience working with Claude or equivalent large language model tools is required; candidates must be comfortable leveraging AI to enhance productivity, research, and communication.

Responsabilidades

• Own recurring credit bureau furnishing operations, including data preparation, validation, submissions, bureau feedback, exception resolution, and reconciliation.
• Build, maintain, and debug SQL transformations, Python scripts, and datapipelines that produce credit reporting data.
• Trace discrepancies from account activity and source records through transformation logic to furnished outputs; identify root causes and implement lasting fixes.
• Investigate escalations from Customer Service, explain what happened to account data and what should be reported under approved policies, and provide evidence to support their dispute responses.
• Identify all accounts affected by reporting defects, implement corrections and controlled reprocessing, and verify the resulting reporting outcomes.
• Develop automated tests, reconciliations, monitoring, and alerts to catch inaccurate, incomplete, duplicate, or unexpected reporting before submission.
• Partner with Engineering on defects in production services or the consumer app, providing reproducible examples, affected-account analysis, and clear requirements; validate fixes through the reporting pipeline.
• Work with Compliance to translate approved reporting requirements into technical rules and elevate ambiguous reporting scenarios.
• Document reporting logic, data lineage, procedures, and incident resolutions so the process is repeatable and can be supported by others.

Conocimientos

SQL

Python

Data pipelines

Data transformations

Troubleshooting

Communication

AI tools (Claude)

Educación

Bachelor's degree in CS/Engineering/DS

Herramientas

dbt

Redshift

PostgreSQL

AWS

Orchestration tools

Descripción del empleo

Sezzle is seeking a Senior Data Engineer in Mexico to own data pipelines, transformations, and reporting that furnish customer account information to credit bureaus. You will work in a fast-growing team, debugging SQL and Python workflows, partnering with Customer Service, Compliance, and Engineering to resolve issues and deliver reliable reporting.

You will lead data-driven improvements, implement automated tests, and ensure data quality across the credit reporting stack while leveraging AI