Senior Manager, Data Architecture & Engineering

Company Description

Publicis Sapient is a digital transformation partner helping established organizations get to their future, digitally enabled state, both in the way they work and the way they serve their customers. We help unlock value through a start-up mindset and modern methods, fusing strategy, consulting, and customer experience with agile engineering and problem-solving creativity. United by our core values and our purpose of helping people thrive in the brave pursuit of next, our 20,000+ people in 53 offices around the world combine experience across technology, data sciences, consulting, and customer obsession to accelerate our clients’ businesses through designing the products and services their customers truly value.

Overview

Data is a strategic asset that powers decision-making across trading, risk management, finance, operations, and enterprise reporting. As we continue to modernize our data ecosystem, we're investing in scalable cloud-native platforms, modern data products, and enterprise architecture capabilities that enable trusted, accessible, and business-ready data across the organization.

As a Senior Manager, Enterprise Data Architecture & Engineering, you will play a critical role in defining the future state of our data landscape. You will lead the development of enterprise architecture standards, guide modern Lakehouse and cloud platform strategies, and help shape the data foundations that support analytics, business intelligence, operational reporting, and emerging AI capabilities.

Working closely with business leaders, architects, engineers, and technology stakeholders, you will influence enterprise-wide data initiatives, drive architecture decisions for complex business domains, and help establish a scalable framework for long-term growth and innovation.

This is a highly visible opportunity for an experienced data leader who enjoys solving complex enterprise challenges, driving modernization, and shaping the future of data across an organization.

Responsibilities

Key Responsibilities

Enterprise Data Architecture & Strategy

• Lead the design, governance, and evolution of enterprise-wide data architecture strategies aligned to business and technology objectives.
• Develop and maintain current-state and future-state architecture roadmaps across data platforms, integrations, analytics environments, and reporting ecosystems.
• Establish architecture principles, standards, reusable patterns, and best practices that support consistency and scalability across the enterprise.
• Provide architecture leadership for large-scale modernization, cloud transformation, and data platform initiatives.
• Partner with technology and business leaders to align architecture investments with strategic priorities and long-term organizational goals.

Lakehouse & Modern Cloud Data Platforms

• Define and guide implementation of scalable Lakehouse architecture strategies utilizing modern cloud-native technologies.
• Lead architecture decisions related to data ingestion, storage, processing, security, governance, and data consumption.
• Drive architectural approaches that support performance, scalability, resiliency, maintainability, and operational excellence.
• Partner with engineering teams to establish reference architectures, design standards, and implementation frameworks.
• Evaluate emerging technologies and recommend modernization opportunities that enhance enterprise data capabilities.

Trading, Market & Enterprise Data Integration

• Architect enterprise solutions supporting energy trading, commodity trading, market operations, risk management, settlements, scheduling, and financial reporting.
• Design end-to-end integration architectures connecting trading platforms, ERP systems, operational technologies, analytical platforms, and external data providers.
• Lead architecture reviews for complex integration initiatives involving enterprise and trading-related systems.
• Establish scalable integration patterns supporting batch, micro-batch, event-driven, and near-real-time data movement.
• Ensure enterprise data architectures support consistency, traceability, quality, and business agility across interconnected platforms.

Data Modeling & Data Products

• Lead enterprise data modeling initiatives including conceptual, logical, and physical data model design.
• Define domain-driven architecture approaches that support scalable business domains and modern Data Product operating models.
• Establish standards governing master, reference, transactional, operational, and analytical data structures.
• Partner with business stakeholders, product teams, and engineering leaders to design reusable, governed, and business-aligned data products.
• Promote architecture practices that improve data discoverability, reuse, accessibility, and trust across the organization.

Data Governance, Quality & Stewardship

• Define architecture standards supporting metadata management, lineage, data quality, governance, security, and regulatory compliance requirements.
• Partner with governance organizations and business stakeholders to establish enterprise stewardship and accountability models.
• Drive adoption of data cataloging, lineage management, observability, and quality monitoring capabilities.
• Ensure architecture decisions support enterprise governance objectives while enabling scalability and business agility.
• Champion practices that improve data transparency, reliability, consistency, and compliance across the enterprise.

Data Engineering & Platform Architecture

• Define architecture standards for batch, micro-batch, streaming, and event-driven data integration solutions.
• Guide engineering teams on scalable pipeline architectures, platform design patterns, and optimization strategies.
• Review and approve solution designs involving ETL/ELT frameworks, cloud-native services, streaming integrations, and enterprise data platforms.
• Establish engineering standards supporting reliability, observability, security, maintainability, and operational support.
• Partner with engineering leadership to ensure architectural designs are effectively implemented across delivery teams.

Leadership & Strategic Influence

• Develop multi-year data architecture roadmaps and implementation strategies supporting the organization's evolving data vision.
• Lead architecture workshops, design reviews, governance forums, and stakeholder alignment sessions.
• Mentor architects, engineers, and technical leaders while helping build organizational architecture maturity.
• Influence enterprise technology decisions and provide thought leadership across business and technology functions.
• Communicate architecture strategies, investment recommendations, and modernization plans to senior technology and business stakeholders.
• Serve as a trusted advisor on enterprise data strategy, platform modernization, and information architecture initiatives.

Qualifications

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical discipline.
• 12+ years of experience in Data Architecture, Data Engineering, Enterprise Data Platforms, or related technical leadership roles.
• Proven experience defining and implementing enterprise-scale data architecture strategies.
• Strong background in cloud-native data platforms, enterprise integration, and modern data ecosystems.
• Experience leading architecture decisions across complex, multi-domain business environments.
• Deep understanding of data modeling, integration architecture, governance, and modern data platform design.
• Demonstrated ability to influence senior stakeholders and lead enterprise-wide technology initiatives.
• Excellent communication, leadership, stakeholder management, and strategic planning skills.

Preferred Qualifications

• Experience within Energy, Oil & Gas, Utilities, Commodity Trading, Capital Markets, or other highly data-intensive industries.
• Deep expertise in modern Data Product, Data Mesh, and domain-driven architecture concepts.
• Experience designing and implementing enterprise cloud data platforms leveraging:
• Databricks
• Azure Data Platform Services
• AWS Data Services
• Snowflake
• Familiarity with real-time, event-driven, and streaming architecture patterns.
• Experience establishing architecture governance boards, reference architectures, design standards, and enterprise best practices.
• Experience leading cloud migration, modernization, and enterprise transformation initiatives.
• Architecture certifications in major cloud platforms and Databricks strongly preferred.

Additional Information

Level: Senior Manager

Compensation: Depending on experience: $160,000 - 210,000

Benefits of Working Here

• An inclusive workplace that promotes diversity and collaboration.
• Access to ongoing learning and development opportunities.
• Competitive compensation and benefits package.
• Flexibility to support work-life balance.
• Comprehensive health benefits for you and your family.
• Generous paid leave and holidays.
• Wellness program and employee assistance.

The range shown represents a grouping of relevant ranges currently in use at Publicis Sapient. Actual range for this position may differ, depending on location and specific skillset required for the work itself.

As part of our dedication to an inclusive and diverse workforce, Publicis Sapient is committed to Equal Employment Opportunity without regard for race, color, national origin, ethnicity, gender, protected veteran status, disability, sexual orientation, gender identity, or religion. We are also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at hiring@publicis.sapient.com