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 - Data Pipeline Development: Design, build, and maintain reliable, scalable ETL/ELT workflows that process batch and streaming data from diverse sources.

- Data Warehousing & Modeling: Design efficient, production-ready schemas (normalized and denormalized) in Snowflake to optimize query performance and enable enterprise analytics.

- API & Event Integration: Connect and ingest data from third-party REST APIs, event-driven streams, and batch sources into core data storage platforms.

- Orchestration: Maintain and expand workflow orchestration pipelines using modern tools (Airflow, Prefect, or Dagster).

- Data Quality & Observability: Implement automated testing, validation, lineage tracking, and proactive alerting frameworks to guarantee data accuracy and system uptime.

- DataOps & Engineering Standards: Drive CI/CD best practices, maintain code bases using Git and Docker, and adopt basic Infrastructure-as-Code (IaC) patterns.





- Code Excellence: Apply modern software engineering standardsincluding design patterns, automated unit/integration testing, and clear documentationto data repositories.

MUST HAVES - 4+ years of experience as a Data Engineer.

- Core Python Fundamentals: Demonstrable expertise writing modular, maintainable, and well-tested Python code (OOP/functional patterns, package management, standard testing frameworks).

- Advanced SQL & Modeling: Deep knowledge of complex SQL queries, query optimization, database design principles, and normalization/denormalization patterns.

- Data Warehousing: Solid, hands-on experience building, managing, and optimizing data architectures within Snowflake.

- Workflow Orchestration: Production experience using workflow orchestration engines like Apache Airflow, Prefect, or Dagster.

- Integrations & Ingestion: Hands-on experience working with REST APIs, event-driven architectures, and both batch and streaming pipelines.

- Data Quality & Lineage: Experience building automated data quality checks, data lineage, and alerting mechanisms (e.g., using tools like dbt test, Great Expectations, or similar).

- DevOps / DataOps Practices: Strong skills in version control (Git), containerization (Docker), CI/CD automation, and familiarity with Infrastructure-as-Code basics.

- Upper-intermediate English level.

NICE TO HAVES - Experience with dbt (data build tool) for data transformations.

- Familiarity with major cloud providers (AWS, GCP, or Azure).

- Exposure to message streaming tech like Apache Kafka or AWS Kinesis.

PERKS AND BENEFITS - Growth without limits:



build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget - Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews - Flexibility: work 100% remotely with adaptable hours that support focus, autonomy, and a healthy work rhythm - Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands - Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized - Well-being & support: access local well-being programs and people-focused support tailored to your location

Data Engineer
Data Engineering core experience: At least 4+ years of experience as a Data Engineer.

Core Python Fundamentals: Demonstrable expertise writing modular, maintainable, and well-tested Python code (OOP/functional patterns, package management, standard testing frameworks).

Advanced SQL & Modeling: Deep knowledge of complex SQL queries, query optimization, database design principles, and normalization/denormalization patterns.

Data Warehousing: Solid, hands-on experience building, managing, and optimizing data architectures within Snowflake.

Workflow Orchestration: Production experience using workflow orchestration engines like Apache Airflow, Prefect, or Dagster.

Integrations & Ingestion: Hands-on experience working with REST APIs, event-driven architectures, and both batch and streaming pipelines.

Data Quality & Lineage: Experience building automated data quality checks, data lineage, and alerting mechanisms (e.g., using tools like dbt test, Great Expectations, or similar).

DevOps / DataOps Practices: Strong skills in version control (Git), containerization (Docker), CI/CD automation, and familiarity with Infrastructure-as-Code basics.

Required Skill Profession

Other General

📌 Senior Data Engineer (León)
🏢 Agileengine
📍 León