Senior Data Engineer ID71670

AgileEngine; Monterrey; Híbrido; MXN 1.869.000 - 2.719.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Professional growth

Competitive compensation

Exciting projects

Flextime

Descripción de la vacante

AgileEngine in Monterrey, Mexico is seeking a Senior Data Engineer to architect, build, and scale a modern data platform. You will design ETL/ELT pipelines, optimize Snowflake schemas, and implement DataOps practices to ensure reliability and accessibility.

You will orchestrate workflows with Airflow, Prefect, or Dagster, apply CI/CD and Docker standards, and ship clean, well-tested Python code that supports enterprise analytics with robust data quality and lineage.

Formación

• 4+ years of experience as a Data Engineer.
• Strong proficiency in Python, including modular, well-tested code.
• Advanced knowledge of SQL, query optimization, database design, and normalization/denormalization patterns.
• Hands-on experience with Snowflake.
• Production experience with workflow orchestration tools like Apache Airflow, Prefect, or Dagster.
• Experience with REST APIs, event-driven architectures, and batch/streaming pipelines.
• Experience implementing automated data quality checks, data lineage, and alerting mechanisms.
• Strong experience with Git, Docker, CI/CD automation, and IaC fundamentals.
• Upper-intermediate English level.

Responsabilidades

• Design, build, and maintain reliable ETL/ELT workflows for diverse data sources.
• Design production-ready Snowflake schemas to support analytics.
• Ingest data from REST APIs, event streams, and batch sources into core storage.
• Maintain and expand workflow orchestration pipelines using Airflow, Prefect, or Dagster.
• Implement automated data testing, lineage tracking, and alerting for data quality and uptime.
• Drive CI/CD best practices, manage code with Git and Docker, and apply IaC patterns.
• Follow modern software engineering standards and document clearly.

Conocimientos

Python

SQL

Snowflake

Airflow

Prefect

Dagster

Docker

CI/CD

REST APIs

DataOps

Herramientas

Git

Docker

Airflow

Descripción del empleo

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

WHY JOIN US

If you’re looking for a place to grow, make an impact, and work with people who care, we’d love to meet you!

ABOUT THE ROLE

We are looking for a Senior Data Engineer to architect, build, and scale a modern data platform — designing production-grade ETL/ELT pipelines, optimizing Snowflake data warehouse schemas, and establishing robust DataOps practices. You will orchestrate workflows using Airflow, Prefect, or Dagster, implement data quality and lineage frameworks, integrate third-party REST APIs and event-driven sources, and apply software engineering standards including CI/CD, Docker, and automated testing to data repositories. The role prioritizes clean, well-tested Python code and a deep commitment to data reliability and accessibility.

WHAT YOU WILL DO

• Design, build, and maintain reliable, scalable ETL/ELT workflows that process batch and streaming data from diverse sources;
• Design production-ready normalized and denormalized schemas in Snowflake to optimize query performance and support enterprise analytics;
• Connect and ingest data from third-party REST APIs, event-driven streams, and batch sources into core data storage platforms;
• Maintain and expand workflow orchestration pipelines using Airflow, Prefect, or Dagster;
• Implement automated data testing, validation, lineage tracking, and proactive alerting frameworks to ensure data accuracy and system uptime;
• Drive CI/CD best practices, maintain codebases using Git and Docker, and adopt Infrastructure-as-Code patterns;
• Apply modern software engineering standards, including design patterns, automated unit and integration testing, and clear documentation.

MUST HAVES

• 4+ years of experience as a Data Engineer ;
• Strong proficiency in Python , including modular, maintainable, and well-tested code;
• Advanced knowledge of SQL, query optimization, database design principles, and normalization/denormalization patterns ;
• Hands-on experience with Snowflake ;
• Production experience with workflow orchestration tools such as Apache Airflow, Prefect, or Dagster ;
• Experience working with REST APIs, event-driven architectures, and batch and streaming pipelines ;
• Experience implementing automated data quality checks, data lineage, and alerting mechanisms ;
• Strong experience with Git, Docker, CI/CD automation, and Infrastructure-as-Code fundamentals ;
• Upper-intermediate English level.

NICE TO HAVES

• Experience with dbt for data transformations;
• Familiarity with major cloud platforms such as AWS, GCP, or Azure;
• Experience with message streaming technologies such as Apache Kafka or AWS Kinesis.

PERKS AND BENEFITS

• Professional growth : Mentorship, TechTalks, and personalized growth roadmaps.
• Competitive compensation : USD-based pay with education, fitness, and team activity budgets.
• Exciting projects : Modern solutions with Fortune 500 and top product companies.
• Flextime : Flexible schedule with remote and office options.