Lead Engineer (Data Lifecycle Management)

Role Overview: As a Lead Engineer (Data Lifecycle Management) , you will take a hands-on role in designing, building, and operating data platform capabilities that govern how data is created, classified, used/shared, retained, archived, and deleted within scope. You will lead delivery of lifecycle controls-such as metadata capture and lineage, data classification and policy enforcement, retention/legal hold workflows, and audit-ready evidence and reporting-embedded directly into modern data stacks (cloud storage, lakehouse/warehouse, and data pipelines). Your expertise will be pivotal in turning governance, privacy, and regulatory requirements into scalable engineering patterns and automation, improving data trust, reducing operational risk, and enabling compliant reuse of data products. The ideal candidate is a hands-on technical leader and mentor who partners closely with data governance, security, privacy, legal, and platform teams to deliver reliable, outcome-driven lifecycle solutions.

Recruiting for this role ends on 5/29/26.

Key Responsibilities:

Outcome-Driven Accountability: Embrace and drive a culture of accountability for customer and business outcomes. Develop engineering solutions that solve complex problems with valuable outcomes, ensuring high-quality, lean designs and implementations.

Technical Leadership and Advocacy: Serve as the technical advocate for products, ensuring code integrity, feasibility, and alignment with business and customer goals. Lead requirement analysis, contributing to low-level architecture and component design, development, unit testing, integrations, and support.

Engineering Craftsmanship: Maintain accountability for the integrity of code design, implementation, quality, data, and ongoing maintenance and operations. Stay hands-on, self-driven, and continuously learn new approaches, languages, and frameworks. Create technical specifications, and write high-quality, supportable, scalable code and review code of other engineers, mentoring them, to ensure all quality KPIs are met or exceeded. Demonstrate collaborative skills to work effectively with diverse teams.

Customer-Centric Engineering: Develop lean engineering solutions through rapid, inexpensive experimentation to solve customer needs. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time.

Incremental and Iterative Delivery: Adopt a mindset that favors action and evidence over extensive planning. Utilize a leaning-forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions.

Cross-Functional Collaboration and Integration: Work collaboratively with empowered, cross-functional teams including product management, experience, and delivery. Integrate diverse perspectives to make well-informed decisions that balance feasibility, viability, usability, and value. Foster a collaborative environment that enhances team synergy and innovation.

Advanced Technical Proficiency: Possess deep expertise in modern software engineering practices and principles, including Agile methodologies and DevSecOps to deliver daily product deployments using full automation from code check-in to production with all quality checks through SDLC lifecycle. Strive to be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate strong understanding of the full lifecycle product development, focusing on continuous improvement and learning.

Domain Expertise: Quickly acquire domain-specific knowledge relevant to the business or product. Translate business/user needs, architectures, and UX/UI designs into technical specifications and code. Be a valuable, flexible, and dedicated team member, supportive of teammates, and focused on quality and tech debt payoff.

Effective Communication and Influence: Exhibit exceptional communication skills, capable of articulating complex technical concepts clearly and compellingly. Inspire and influence teammates and product teams through well-structured arguments and trade-offs supported by evidence. Create coherent narratives that align technical solutions with business objectives.

Engagement and Collaborative Co-Creation: Engage and collaborate with product engineering teams at all organizational levels, including customers as needed. Build and maintain constructive relationships, fostering a culture of co-creation and shared momentum towards achieving product goals. Align diverse perspectives and drive consensus to create feasible solutions.

The team: US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value/outcomes that leverages a progressive and responsive talent structure. As Deloitte's primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results and outcomes. It helps power Deloitte's success. It is the engine that drives Deloitte, serving many of the world's largest, most respected companies. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence.

Key Qualifications:

• A bachelor's degree in computer science, software engineering, or a related discipline. An advanced degree (e.g., MS) is preferred but not required. Experience is the most relevant factor.

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• Excellent software engineering foundation with deep understanding of OOP/OOD, sequence/activity/state/ER/DFD diagrams, data-structure, algorithms, code instrumentations, etc.
• 8+ years proven experience with Python, SQL/NoSQL.
• 8+ years of experience with cloud-native engineering and understanding of Azure Data Pipelines/the Azure Portal Environment.
• 8+ years delivering governed data platforms.
• 2+ years of experience with AI/ML and GenAI.
• Strong understanding of methodologies & tools like, XP, Lean, SAFe, DevSecOps, SRE, ADO, GitHub, SonarQube, etc. to deliver high quality products rapidly.
• Deep experience with at least one modern data platform and its governance controls (e.g., Databricks, Snowflake, BigQuery, Redshift, Synapse).
• Experience with implementing data governance and lifecycle management controls across Microsoft 365 (M365) applications including Teams, OneDrive, SharePoint, CoPilot, etc.

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• Experience with governance tools like Microsoft Purview.
• Excellent interpersonal and organizational skills, with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care.
• Limited immigration sponsorship may be available
  
  

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $107,700 to $221,200.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html

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