About the Role

We are looking for a Senior Data Engineerto 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 standards—including design patterns, automated unit/integration testing, and clear documentation—to 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

- Professional growth

Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps
- Competitive compensation

We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities
- A selection of exciting projects

Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands
- Flextime

Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.

📌 Senior Data Engineer (México)
🏢 Agileengine
📍 México