Senior Data Engineer

• Take charge of day-to-day team activities including scrum ceremonies, sprint planning, and backlog management

• Oversee the development and operation of modern data engineering solutions, including data ingestion, processing, integration, and governance

• Collaborate with stakeholders to identify business needs and develop solutions that meet those needs

Community of practice contribution

• Develop and maintain shared frameworks for data engineering; contributions should reflect design for broader organisational scope, not just the immediate team

• Contribute to the onboarding of new data engineers, analysts, product owners, and other team members joining the project

• Contribute to community-of-practice enablement programs — including internal upskilling and certification, training frameworks, and knowledge-sharing initiatives

• Act as a data owner and functional subject matter expert for assigned areas, supporting data product certification and lineage maturity

Platform & operations

• Ensure platform stability and operational SLAs; drive reduction in operational noise and manual intervention

• Extend DevOps capabilities for deploying and operating data solutions

• Work closely with product owners and stakeholders to identify and mitigate potential data challenges

• Support the adoption of AI and LLM-based tooling to improve engineering efficiency and data quality

Qualifications

Education

• Bachelor's degree or higher in Computer Science, Statistics, Business, Information Technology, or a related field

Experience

• 5+ years of experience in data engineering or a related discipline, with at least 2 years in a technical lead or team lead capacity

• Proven track record delivering and supporting software and data engineering capabilities in a fast-paced, dynamic environment

• Experience contributing to shared frameworks within the data domain, and creating data assets used in mission-critical applications

Technical skills

• Intermediate data design skills — data modelling, schema design, and pipeline architecture for enterprise-scale solutions

• Core Python proficiency — including object-oriented programming, reusable library design, and clean scalable code; not just ad hoc scripting

• Advanced SQL — window functions, query optimisation, and complex transformation logic beyond basic CRUD operations; experience with dbt is a plus

• Intermediate DevOps and cloud (Azure, AWS, or GCP) — including CI/CD pipeline ownership, deployment practices, and cloud cost awareness

• Experience with Agile methodologies; hands-on experience running scrum ceremonies

• Experience with automated testing and data testing frameworks — able to design and enforce test coverage across pipelines and data assets

Domain expertise

• 5+ years building enterprise data solutions with a proven track record delivering high-quality pipelines and analytics products

• Familiarity with modern orchestration and transformation tooling — Dagster, dbt, and Snowflake experience strongly preferred

• Understanding of data warehousing concepts and architecture patterns such as medallion architecture and dimensional modelling

• Awareness of data product concepts including lineage, certification, and operational telemetry

• Experience implementing data quality frameworks — including validation, profiling, and monitoring — to ensure integrity and consistency across data systems

• Experience working in environments where data engineering capabilities are shared as platform services, not built in isolation

Individual skills

• Strong collaborator and team player, with the ability to work effectively with business stakeholders and cross-functional teams

• Strong analytical thinker — able to troubleshoot complex pipeline issues, optimise performance, and identify improvement opportunities across data systems

• Clear point of view on data engineering best practices — and the ability to bring others along, not just hold the opinion

• Effective communicator who can translate technical decisions into business language

Mindsets and behaviours

• Embraces change and is passionate about driving innovation and continuous improvement

• Believes in a non-hierarchical culture of collaboration, transparency, safety, and trust

• Not afraid to take risks and try new approaches; willing to learn from failure and use it to drive growth

• Invested in the growth of others — sees enabling teammates as part of their own success

Location(s)

Mexico City - Antara Tower A - 5th Floor - Local Office

Kraft Heinz is an Equal Opportunity Employer – Underrepresented Ethnic Minority Groups/Women/Veterans/Individuals with Disabilities/Sexual Orientation/Gender Identity and other protected classes.