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About the role
Role Overview: As the Manager, Software Engineering (Data Engineering) for our client, you will lead high-performing data engineering teams to deliver secure, scalable, and reliable data products, pipelines, and platforms. Your focus will be on enabling critical analytics, AI/ML, and digital experiences by building and operating production-grade data solutions that drive key customer and associate outcomes. Your role will involve providing technical direction, shaping data architectures, guiding design and code quality, and ensuring robust data engineering practices on cloud. Key Responsibilities: - Lead and grow the team: Coach and develop data engineers through regular 1:1s, feedback, and career development to build an engaged, inclusive, high-performing team. - Own delivery outcomes: Ensure teams consistently meet commitments on data quality, reliability, security, and time-to-market for data pipelines, platforms, and products. - Provide technical direction: Guide architecture and design decisions across data pipelines, data models, and data platforms to ensure robust, maintainable, and cloud-ready solutions. - Set engineering standards: Define and enforce standards for data engineering design, coding, code review, testing, documentation, and operational readiness. - Drive DevSecOps and data delivery practices: Embed secure engineering, automated testing, data validation, and policy checks into CI/CD pipelines and data deployment workflows using Git-based tooling. - Own cloud-based data delivery: Ensure data solutions are designed and operated for cloud, leveraging managed data services, lakehouse patterns, and infrastructure-as-code where appropriate. - Strengthen production operations: Champion observability, performance, resiliency, incident management, and post-incident learning for data platforms and pipelines in production. - Use metrics to improve: Track and act on delivery, data quality, stability, and productivity metrics to refine ways of working and remove bottlenecks. - Partner across the ecosystem: Work closely with product, architecture, analytics, security, infrastructure, and business stakeholders to align priorities, manage dependencies, and communicate risks and trade-offs clearly. - Foster a culture of learning and experimentation: Encourage engineers to grow skills in cloud, data platforms, and automation, and to share knowledge across teams. Qualifications Required: - 8+ years of experience delivering software or data solutions using Agile, Lean, and DevSecOps practices. - 3+ years of direct people leadership experience managing engineering teams (data engineering preferred), including hiring, coaching, performance management, and career development. - Demonstrated strength in execution leadership, setting clear goals, making timely decisions, managing risk, and honoring commitments across multiple initiatives. - Experience influencing and partnering in matrixed environments with various stakeholders. - Technical skills in data engineering, including modern data engineering and platforms, cloud-native data architectures and platforms, and proficiency in programming languages such as Python, Scala, or Java. - Strong understanding of data security and privacy practices, experience working in regulated environments, and familiarity with observability tooling and practices for data systems. - Exposure to additional data tools and frameworks is a plus, as well as familiarity with machine learning, analytics, or BI use cases. (Note: Any additional details of the company were not included in the provided job description) Role Overview: As the Manager, Software Engineering (Data Engineering) for our client, you will lead high-performing data engineering teams to deliver secure, scalable, and reliable data products, pipelines, and platforms. Your focus will be on enabling critical analytics, AI/ML, and digital experiences by building and operating production-grade data solutions that drive key customer and associate outcomes. Your role will involve providing technical direction, shaping data architectures, guiding design and code quality, and ensuring robust data engineering practices on cloud. Key Responsibilities: - Lead and grow the team: Coach and develop data engineers through regular 1:1s, feedback, and career development to build an engaged, inclusive, high-performing team. - Own delivery outcomes: Ensure teams consistently meet commitments on data quality, reliability, security, and time-to-market for data pipelines, platforms, and products. - Provide technical direction: Guide architecture and design decisions across data pipelines, data models, and data platforms to ensure robust, maintainable, and cloud-ready solutions. - Set engineering standards: Define and enforce standards for data engineering design, coding, code review, testing, documentation, and operational readiness. - Drive DevSecOps and data delivery practices: Embed secure engineering, automated testing, data valida