Senior Data Engineer ID71670

AgileEngine, LLC.; León; Presencial; MXN 900.000 - 1.200.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Professional growth

Competitive compensation (USD-based)

Flextime: remote and office options

Exciting projects

Descripción de la vacante

AgileEngine, LLC. is seeking a Senior Data Engineer to design, build, and scale a modern data platform. You will architect ETL/ELT pipelines, optimize Snowflake schemas, and enforce DataOps practices with CI/CD, Docker, and automated testing.

You will orchestrate workflows with Airflow, Prefect, or Dagster, ingest data from REST APIs and event streams, and emphasize clean, well-tested Python code for reliability and accessibility.

Formación

• 4+ years of experience as a Data Engineer.
• Proficiency in Python with well-tested code.
• SQL, data modeling, and Snowflake schemas.
• Experience with REST APIs, event-driven sources, and pipelines.

Responsabilidades

• Design, build, and maintain scalable ETL/ELT workflows.
• Create production-ready Snowflake schemas for analytics.
• Ingest data from REST APIs, event streams, and batch sources.
• Maintain Airflow/Prefect/Dagster pipelines and CI/CD.
• Implement data quality checks, lineage, and alerting.
• Follow Git, Docker, and IaC practices and document clearly.

Conocimientos

Python

SQL

Snowflake

Apache Airflow

Prefect

Dagster

REST APIs

Git

Docker

CI/CD

Infrastructure-as-Code

Data quality checks

Data lineage

Herramientas

Airflow

Prefect

Dagster

Snowflake

Git

Docker

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;

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.