Big Data Engineering Lead

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

📋 Description

• Provide technical guidance for the engineering delivery and quality assurance of the Data Foundation platform.

• Lead a team in developing and sustaining enterprise data pipelines, data products, canonical data models, and data services.

• Facilitate analytics, AI, integration, and operational reporting through scalable data solutions.

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

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

• Drive engineering execution, solution quality, operational reliability, and foster a high-performing data engineering team.

• Meet Data Foundation engineering commitments.

• Enhance data pipeline reliability, performance, and scalability.

• Improve data quality across enterprise data assets.

• Advocate for engineering standards and best development practices.

• Mitigate technical debt and engineering risks.

• Enhance operational stability and minimize incidents.

• Promote engagement, capability development, and retention within the engineering team.

• Increase 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 in guiding engineering teams or large-scale data initiatives.

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

• Experience working in agile software development environments.

• Advanced proficiency in SQL and data modeling.

• Strong development experience with Python and PySpark.

• In-depth understanding of ETL and ELT architecture patterns.

• Experience in implementing Master Data Management solutions.

• Proficient in building RESTful APIs and data services.

• Familiarity with GraphQL and contemporary integration methods.

• Understanding of microservices-based architectures.

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

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

• Proficient in English.

• Excellent technical leadership and mentoring abilities.

• Strong problem-solving and decision-making skills.

• Ability to balance delivery commitments with the long-term sustainability of the platform.

• Strong collaboration and stakeholder engagement skills.

• Exceptional written and verbal communication skills.

• A passion for engineering excellence and continuous improvement.

🏝️ Benefits

• No benefits or compensation extras explicitly stated.