Lead Data Engineer

What you will do

Develop, implement, and operationalize the strategic roadmap for the data platform, translating long-term architectural vision into executable initiatives and measurable outcomes;
Build and evolve Lakehouse, ETL, streaming, and MDM capabilities, lead modernization programs, and drive the delivery of scalable data products and platform services;
Work closely with engineering teams throughout design, development, testing, deployment, and production support to ensure platform solutions meet performance, reliability, governance, and business requirements;

What you need

Degree in Computer Science, Computer Engineering, Information Systems, Systems Development Analysis, or related fields;
Advanced English;
Strong experience designing and implementing large-scale ETL and data platform architectures;
Extensive experience with Databricks and modern Lakehouse architectures;
Strong cloud experience with Azure, AWS, and/or Google Cloud Platform;
Experience with Master Data Management (MDM), entity resolution, matching and survivorship strategies, and data governance principles;
Deep understanding of data modeling, distributed data processing, orchestration frameworks, and data platform scalability;
Experience designing data contracts, schema evolution strategies, and reusable data platform components;
Strong software engineering fundamentals, including testing, CI/CD, code quality, observability, and operational excellence;
Experience establishing data quality frameworks, validation layers, reconciliation processes, and reliability standards;
Knowledge of streaming architectures, event-driven systems, and modern data integration patterns;
Proven experience mentoring engineers and providing technical leadership across multiple teams;
Ability to evaluate architectural trade-offs, identify long-term risks, and design solutions aligned with business growth objectives;
Experience working in highly scalable and mission-critical environments.

Serve as the primary technical reference for Data Engineering and Data Platform initiatives;
Mentor and develop engineers through technical coaching, architecture reviews, and best practice guidance;
Define engineering standards and ensure consistency across teams and domains;
Establish expectations for production readiness, code reviews, testing, reliability, and maintainability;
Foster a culture of technical excellence, ownership, continuous improvement, and collaboration;
Drive alignment between engineering teams on architecture, platform standards, and long-term technical direction;
Balance strategic thinking with hands-on execution, actively contributing to critical implementations when needed.

Strong analytical thinking and problem-solving skills;
Excellent communication and stakeholder management abilities;
Ability to influence technical decisions across teams and organizational levels;
Collaborative leadership style with a mentorship mindset;
Strong sense of ownership and accountability;
Ability to navigate ambiguity and make sound engineering decisions;
Results-oriented mindset with focus on scalability, quality, and business impact.

Experience leading enterprise-scale Data Engineering and MDM transformation initiatives;
Experience defining multi-year technology roadmaps and platform modernization strategies;
Hands-on experience transitioning architectures from batch processing to streaming solutions;
Experience with multi-region, multi-brand, or highly regulated data environments;
Strong understanding of data product architecture and domain-oriented data design principles;
Experience influencing executive stakeholders and driving strategic technology decisions;
Significant experience building and operating business-critical, high-scale data platforms;
Deep understanding of software engineering best practices and engineering excellence at scale.