Data Engineer

Time To Hire; Ciudad de México; Híbrido; MXN 700.000 - 1.100.000; Jornada completa

Descripción de la vacante

Time To Hire in Mexico City is seeking a Data Engineer to help build and scale the data infrastructure behind a fast-growing payments platform. You’ll own meaningful parts of the data platform end to end—from ingestion and modeling to quality, monitoring, and reliability.

You’ll work with high-volume, business-critical data and own the data pipeline stack, collaborating with Analytics, Data Science, Risk, and Fraud teams. Strong SQL/Python skills and experience with Airflow/dbt are required.

Formación

• 3–5 years of experience as a Data Engineer or similar role with production pipelines.
• Strong ownership of data systems end to end.
• Advanced SQL and Python skills.
• Hands-on with Airflow and dbt.
• Experience with AWS or GCP and warehouses like Redshift/BigQuery/Snowflake.
• Knowledge of data modeling (dimensional and layered/medallion).
• Relational and NoSQL databases; Git, CI/CD, and Docker.
• Familiar with AI coding tools and English/Spanish fluency.
• Degree or equivalent practical experience in CS/Engineering/Math.

Responsabilidades

• Build and maintain batch and near real-time data pipelines.
• Design observable, scalable data flows with clear SLAs.
• Create layered data models from raw to business-ready.
• Produce trusted datasets for metrics like transactions and settlements.
• Implement data quality, testing, monitoring, and alerting.
• Work with PCI DSS and Mexican regulations; collaborate with Analytics and Risk.
• Monitor platform performance and cloud costs; participate in incident reviews.
• Leverage AI tooling in daily engineering workflow with validation.

Conocimientos

End-to-end data systems ownership

SQL

Python

Educación

Bachelor's degree in Computer Science/Engineering/Math or related field

Herramientas

Apache Airflow

dbt

AWS

GCP

Redshift

BigQuery

Snowflake

PostgreSQL

MySQL

NoSQL databases

Git

CI/CD

Docker

Claude Code

Cursor

Copilot

Terraform

Descripción del empleo

Data Engineer

Mexico City · 90% Remote Mid-Senior · 3–5 years experience Reports to: Data Lead

About the role

We’re looking for a Data Engineer to help build and scale the data infrastructure behind a fast-growing payments platform in Mexico.

You’ll work with high-volume, business-critical data and own meaningful parts of the data platform end to end—from ingestion and modeling to quality, monitoring, and reliability.

What you’ll do

• Build and maintain batch and near real-time data pipelines from transactional systems, banks, card networks, and partners.

• Design reliable, observable, and scalable data flows with clear SLAs.

• Build layered data models from raw > curated > business-ready.

• Create trusted datasets for metrics such as transaction volume, approval rates, chargebacks, and settlements.

• Implement data quality, testing, monitoring, and alerting.

• Work with sensitive data following PCI DSS and Mexican financial regulations.

• Partner with Analytics, Data Science, Risk, and Fraud teams to support reporting and ML models.

• Monitor platform performance, reliability, and cloud costs.

• Participate in incident response and blameless post-mortems.

• Use AI coding assistants as part of your daily engineering workflow, while validating their output.

What we’re looking for

• 3–5 years of experience as a Data Engineer or similar role, with production data pipelines.

• Strong experience owning data systems end to end.

• Advanced SQL and strong Python skills.

• Hands‑on experience with Apache Airflow and dbt.

• Experience with AWS or GCP and data warehouses such as Redshift, BigQuery, or Snowflake.

• Solid knowledge of data modeling, including dimensional and layered/medallion architectures.

• Experience with relational databases such as PostgreSQL/MySQL and NoSQL databases.

• Good engineering practices: Git, code reviews, testing, CI/CD, and Docker.

• Daily experience with AI coding tools such as Claude Code, Cursor, Copilot, or similar.

• Fluent Spanish and professional working English.

• Degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience.

Nice to have

• Experience in payments, fintech, banking, or other high-volume environments.

• Kafka, Debezium, Spark, or Flink.

• Data quality and observability tools such as Great Expectations or Monte Carlo.

• Terraform, Iceberg, or Delta Lake.

• Experience supporting ML pipelines or feature engineering, especially for fraud or risk.

• Exposure to LLM use cases such as embeddings, vector search, or text-to-SQL.

• Familiarity with PCI DSS or the Mexican payments ecosystem, including SPEI, card networks, and acquiring.

Why join?

You’ll work on data where reliability really matters: every transaction represents someone's money. The role combines data engineering, fintech, AI, and high-scale infrastructure, with the opportunity to have direct ownership over critical parts of the platform.