Senior Data Engineer (Python)

Location: Mexico City, Antara Tower A, 5th Floor, Local Office

Company

hirify.global is hiring for a data engineering role focused on enterprise data platforms, pipelines, and analytics solutions.

What you will do

• Lead and mentor a cross-functional team of data engineers.
• Own end-to-end architecture and design decisions for individual data engineering projects.
• Manage scrum ceremonies, sprint planning, backlog activities, and day-to-day delivery.
• Oversee data ingestion, processing, integration, governance, and the operation of enterprise data solutions.
• Develop shared data engineering frameworks and support onboarding, training, certification, and knowledge-sharing programs.
• Improve platform stability, operational SLAs, deployment practices, data quality, and engineering efficiency through DevOps and AI/LLM-based tooling.

Requirements

• Bachelor's degree or higher in Computer Science, Statistics, Business, Information Technology, or a related field.
• At least 5 years of experience in data engineering or a related discipline, including at least 2 years in a technical lead or team lead capacity.
• Experience delivering enterprise data solutions, shared frameworks, mission-critical data assets, and analytics products.
• Intermediate data design, data modelling, schema design, pipeline architecture, DevOps, and cloud experience with Azure, AWS, or GCP.
• Strong Python, advanced SQL, automated testing, data testing, Agile, and scrum facilitation skills.
• Ability to collaborate with business stakeholders, troubleshoot complex pipeline issues, optimise performance, and communicate technical decisions in business language.

Nice to have

• Experience with dbt, Dagster, and Snowflake.
• Knowledge of medallion architecture, dimensional modelling, data lineage, certification, operational telemetry, and data quality frameworks.

Culture & Benefits

• Work in a collaborative, transparent, non-hierarchical environment built on safety and trust.
• Contribute to internal upskilling, certification, training, and knowledge-sharing initiatives.
• Support continuous improvement, experimentation, and the growth of other team members.