Data Engineering Manager - Indaiatuba/SP

As an Engineering Manager in the Enterprise Data Organization (EDO), you will provide technical and people leadership for John Deere Financial data products, partnering closely with product, architecture, and engineering leaders to deliver scalable, secure, and high‑quality solutions.

• Serve as a servant leader for 2–3 agile scrum teams, solving complex analytical and conceptual problems;


• Partner with the Group Engineering Manager and Group Product Manager to deliver against vision, strategy, and roadmap;


• Collaborate with Architects on technology selection, solution design, and alignment to enterprise standards;


• Foster a strong Agile and DevOps culture, monitoring product health, reliability, technical debt, and delivery metrics;


• Identify and remove technical and organizational impediments impacting teams’ execution;


• Lead staffing and capability planning to ensure teams have the right mix of skills;


• Coach, develop, and retain engineering talent through feedback, recognition, and growth opportunities;


• Balance technical, operational, and financial considerations in decision‑making;


• Maintain strong, collaborative relationships across engineering, product, security, and business stakeholders.

• Bachelor's degree in Computer Science, Computer Engineering, MIS, or equivalent;


• Advanced English (broad vocabulary, strong grammar, able to lead meetings, argue, negotiate, and conduct training sessions);


• Strong software engineering background with experience in modern data and cloud platforms, including API, Databricks, Java and/or Python, and AWS;


• Hands‑on experience designing and operating data pipelines and enterprise data lakes;


• Proven ability to provide technical leadership across multiple teams and complex systems;


• Working knowledge of CI/CD pipelines, automation, and DevOps practices;


• Working knowledge of test‑driven development, data quality validation, and test automation;


• Demonstrated experience hiring, developing, and leading engineering teams;


• Strong written and verbal communication skills with the ability to influence across functions;


• Deep understanding of Agile development methodologies and delivery at scale;


• Prior experience leading software or data engineering teams.

• Leadership experience in a product‑aligned, Agile organization;


• Deep hands‑on experience with Databricks and Spark performance optimization;


• Experience building or operating data products, data hubs or data platforms;


• Strong understanding of cloud cost management and performance optimization;


• Exposure to agentic workflows, knowledge graphs, data governance, metadata, or data quality platforms;


• Experience supporting advanced Risk analytics use cases.