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.
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📌 Data Engineer (Xico)
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