Cloud-Native Full-Stack Data Engineer

AstraZeneca; Guadalajara; In loco; MXN 900.000 - 1.300.000; Tempo pieno

Descrizione del lavoro

AstraZeneca is seeking a passionate Full Stack Data Engineer to strengthen our data engineering capabilities. You will build scalable data pipelines, data products, and Python services while aligning with enterprise standards and platform roadmaps.

You will collaborate with architects, analysts, product teams, and other engineers to deliver reliable data products, implement DevOps practices, and ensure quality through testing, observability, and automation.

Competenze

• Strong software engineering and production-grade data solutions experience.
• Proficient in Python for data processing and automation.
• Experience with Snowflake data platforms and related tooling.
• Expert SQL skills for analytics and transformation.
• Familiarity with CI/CD, DevOps, and data Ops practices.
• Ability to translate business requirements into reliable data products.

Mansioni

• Design, build, and support scalable data pipelines and data products.
• Apply software engineering best practices to data solutions.
• Develop Python-based data processing and automation services.
• Own DevOps/DataOps practices including CI/CD and release automation.
• Deliver automated, cost-effective data solutions for analytics.
• Collaborate with data architects and stakeholders on design.
• Test and QA data solutions including unit and integration tests.
• Monitor, troubleshoot, and improve data platforms.
• Share best practices and contribute reusable patterns.

Conoscenze

Software engineering

Python engineering

Snowflake pipelines

SQL analytics

CI/CD pipelines

DevOps/DataOps

Data modeling

Problem solving

Strumenti

dbt

Airflow

AWS Glue

AWS Lambda

Fivetran

Snowflake

Starburst/Trino

Terraform

GitHub Actions

Collibrato

Descrizione del lavoro

AstraZeneca is seeking a passionate Full Stack Data Engineer to strengthen our data engineering capabilities. You will build scalable data pipelines, data products, and Python services while aligning with enterprise standards and platform roadmaps.

You will collaborate with architects, analysts, product teams, and other engineers to deliver reliable data products, implement DevOps practices, and ensure quality through testing, observability, and automation.