Data Engineering Leader

Position Overview

As a Data Engineering Leader, you will serve as both the visionary architect and driving force behind our data strategy—shaping the roadmap and leading its successful implementation. Your impact spans the entire organization with a focus on managing core data platforms, enabling efficient data sharing, and maintaining a secure, high-performance data integration landscape. In this hands-on leadership role, you will set the standard for excellence while mentoring and inspiring engineering teams. Recruitment for this role ends on November 17, 2025. As part of the US Deloitte Technology Product Engineering team, you will contribute to innovative digital solutions that power Deloitte’s success.

Key Responsibilities

• Strategic Vision and Alignment: Craft and articulate a vision for Data Management & Enterprise Integration technologies tailored for product engineering teams in alignment with the US Deloitte Technology Data strategy. Collaborate with stakeholders including product, engineering, experience, delivery, security, and infrastructure teams.
• Advocacy and Technology Roadmap: Develop and communicate the implementation approach for Data Management/Enterprise Integrations. Ensure the organization is well-informed about objectives, KPIs, technology roadmaps, and progress.
• Craft Mastery and Objectives Realization: Define, measure, and drive KPIs. Establish and evolve domain standards and best practices while being hands-on with design, architecture, and code reviews, reducing tech debt, and experimenting with new technologies.
• Capability Evolution and Development: Mentor and develop engineering talent, coach on modern engineering practices related to Data Management & Enterprise Integrations, and lead internal initiatives such as experiments, conference presentations, and publications.
• Iterative Value Delivery: Embrace an iterative approach to product engineering that aligns technical solutions with customer and business goals through incremental steps.
• Customer-Centric Problem Solving: Focus on addressing critical customer issues by aligning technical solutions with business objectives while minimizing unnecessary complexity.
• Expert Proficiency and Continuous Improvement: Leverage deep expertise in software engineering to identify inefficiencies, drive innovation, and enhance a lean, adaptable operating model.
• Tech/Quality Risk Management: Ensure the development of explainable, scalable, reliable, and secure products by managing technology adoption and mitigating potential technical risks.
• Influential Communication: Influence decision-making with clear, structured communication and well-supported technical trade-offs.
• Organizational Engagement and Collaboration: Build collaborative relationships across all organizational levels to co-create momentum and deliver value.

Required Qualifications

• Bachelor’s degree in computer science, software engineering, or a related discipline; experience being the most relevant factor.
• Minimum 10 years of experience in data management, data governance, data structures, database systems, and data modeling.
• Minimum 5 years of experience managing big data using platforms such as SAP HANA, Databricks, Snowflake, or other industry-leading data platforms.
• Minimum 3 years of experience with cloud hyperscalers (AWS, Azure, or GCP) to build cloud-native applications.
• Minimum 2 years of experience leading and managing high-performing data engineering teams.
• Minimum 1 year of experience with AI/ML and GenAI.
• Prior experience implementing advanced data architectures, including zero-copy data sharing, data lakes, and modern ELT strategies.
• Experience with modern software engineering practices and deployment techniques (e.g., Blue-Green, Canary) to support A/B testing strategies.
• Familiarity with Business Context Diagrams, sequence/activity/state/entity relationship/data flow diagrams, OOP/OOD, data structures, algorithms, and code instrumentation.
• Experience with methodologies and tools such as XP, Lean, SAFe, DevSecOps, SRE, ADO, GitHub, and SonarQube for rapid, high-quality product delivery.
• Experience managing transformation projects, particularly migrating between data technology platforms.
• Demonstrated success in mentoring and managing multi-national teams across global time zones and cultures.
• Experience creating a multi-year data strategy in support of organizational data and analytics needs.
• Excellent interpersonal and organizational skills with the ability to handle diverse situations and complex projects with passion, empathy, and care.

Benefits & Perks

• Compensation: Wage range is $130,900 - $268,700, reflecting various factors including skills, experience, and organizational needs.
• Eligibility to participate in a discretionary annual incentive program based on individual and organizational performance.
• Ability to travel approximately 10% as required.
• Limited immigration sponso