Big Data Engineering Lead

This is a fully remote position, open to applicants in Mexico.

📋 Description

• Offer technical guidance, oversee engineering delivery, and ensure quality assurance for the Data Foundation platform.

• Lead the development and upkeep of enterprise data pipelines, data products, canonical data models, and data services.

• Facilitate analytics, AI, integration, and operational reporting via enterprise data solutions.

• Collaborate with the Service Owner, Architecture Team, and Platform Engineering Lead.

• Provide scalable, reliable, and maintainable data solutions that align with enterprise standards and strategic goals.

• Assume responsibility for engineering execution, solution quality, operational dependability, and the development of a high-performing data engineering team.

• Fulfill Data Foundation engineering commitments.

• Guarantee the reliability, performance, and scalability of data pipelines.

• Promote enhancements in data quality, adopt engineering standards, minimize technical debt, and bolster operational stability.

• Enhance the reuse of canonical data models, data products, and engineering frameworks.

⛳️ Requirements

• Over 8 years of experience in data engineering, software engineering, or the development of enterprise data platforms.

• More than 3 years of technical leadership experience directing engineering teams or large-scale data initiatives.

• Demonstrated success in designing and delivering enterprise data platforms, pipelines, and data products.

• Experience working within agile software development frameworks.

• Advanced skills in SQL and data modeling.

• Proficient in Python and PySpark development.

• Extensive knowledge of ETL and ELT architecture patterns.

• Strong technical leadership, coaching abilities, and problem-solving skills.

• Resilient, emotionally intelligent, with a focus on agile delivery.

• Comprehensive understanding of the distinction between coding and engineering.

• Experience with implementing Master Data Management solutions.

• Skilled in building RESTful APIs and data services.

• Familiarity with GraphQL and contemporary integration methodologies.

• Understanding of microservices-based architectures.

• Experience with event-driven and real-time data processing solutions.

• Strong grasp of data quality frameworks, metadata management, and data lineage concepts.

• Familiarity with cloud-native foundations or AI coding assistants.

🏝️ Benefits

• Flexible work arrangements with remote options available.

• Opportunities for continuous learning and professional development.

• Involvement in high-impact projects and intricate engineering challenges.

• International collaboration within a global network of expertise.