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.