VP Engineering - Data Products

dentsu•Chicago, MD

3d•Hybrid

About The Position

We are looking for a senior engineering leader to own the technical roadmap for our enterprise-scale data and AI infrastructure. You will lead a multi-disciplinary engineering organization, set data platform and cloud architecture direction, and act as the bridge between hands-on solution design and commercial/vendor accountability. This role combines strong architectural credibility with people leadership, governance ownership, and stakeholder management across global clients.

Requirements

Strong working knowledge of modern cloud data platforms (Azure Databricks/Spark using Python and associated frameworks, or Snowflake equivalent).
Strong working knowledge of cloud storage solutions (Azure Data Lake, Blob storage, or equivalent).
Strong experience of building data reporting and visualisations using PowerBI, Tableau, or equivalent tools.
Strong knowledge of SQL and data modelling principles.
Experience in application development with proficiency in Python or JavaScript frameworks.
Strong knowledge and experience of hosting in major cloud platforms (Azure, AWS, or GCP).
Familiarity with how AI/ML and agentic systems are integrated with enterprise data platforms.
Solid understanding of data governance, access control, and security practices in cloud environments.
Knowledge of delivering solutions using a microservice architecture with RESTful protocols and event-driven architectures.
Knowledge and experience of implementing Continuous Integration and Continuous Delivery.
Ability to quickly learn and apply emerging programming languages, frameworks, and platforms.
Comfortable working in an agile environment.
Excellent communication and collaboration skills with the ability to explain technical solutions clearly to both technical and business audiences.

Nice To Haves

Proven experience leading data engineering or data platform teams at a senior/head level, ideally within a large or matrixed organization.
Industry experience working with Data platforms is essential, with strong background in dimensional data modelling, data pipeline development and data engineering in support of web applications.
Strong hands-on background in modern cloud data platforms (e.g. Databricks, Snowflake, or equivalent) and major cloud providers (Azure, AWS, or GCP).
Solid understanding of data governance, access control, and security practices in cloud environments.
Experience with large-scale ETL/ELT design and migration programs.
Demonstrated experience with cloud cost management and FinOps practices.
Experience managing vendor contracts, procurement, and commercial negotiations.
Strong stakeholder management skills with the ability to communicate effectively across technical and non-technical audiences and global/matrixed teams.
A structured, specification-driven approach to requirements and delivery, with a preference for disciplined, release-oriented delivery.
Able to demonstrate evidence of applying technology to solve business problems.
Experience in building applications in MERN (Mongo, Express, React, Node) using Webpack, Typescript, and GitHub.
Experience with Docker and/or Kubernetes and containerized deployments (AKS).
Experience with workflow orchestration tools such as Apache Airflow or n8n.
Experience of code quality, test, CI/CD and package managers such as Jest, Lint, Brigade, and Helm.
Experience with Kafka and event-driven architecture patterns.
Experience with identity/access management integrations (Okta, Entra ID).
Experience with service mesh technologies (Istio) and advanced networking patterns.
Working knowledge of GraphQL APIs, ABAC solutions, and CMS platforms.
Experience with C4 model architecture documentation (PlantUML or similar).
TOGAF or other enterprise architecture certification.
Cloud architecture certifications (AWS Certified Solutions Architect, Microsoft Certified: Azure Administrator Associate).
Familiarity with the AdTech/MarTech ecosystem.

Responsibilities

Lead, grow and develop a multi-disciplinary engineering organization, providing mentorship to Development Leads and engineers, ensuring team composition is adequate, and hiring to fill gaps.
Set and own the technical roadmap for the data platform, defining reference architectures and design patterns (e.g. medallion/layered architectures) that scale across multiple business units and data domains.
Provide guidance, coaching and mentorship in modern data engineering practices, web application development, and best practices for diagnostics, debugging, testing, deploying, and troubleshooting.
Work with Product and Engineering teams to scope, plan and estimate the technical roadmap, aligning it to broader business goals and helping to forecast delivery timescales.
Evaluate solution options against business requirements and organizational standards; champion rapid prototyping and proof-of-concept work to validate designs and de-risk delivery.
Provide architectural oversight and mentorship to architects and engineers; maintain high standards of design documentation and contribute to the evolution of architectural reference models.
Foster constructive debates between Product, Engineering and UX teams to create scalable, client-focused solutions that solve business problems with software in the shortest sustainable lead-time.
Establish and run governance frameworks for applications and data products, including certification and stewardship processes; ensure compliance with security, data privacy, and regulatory standards.
Own platform security posture: access control, secrets management, naming/tagging conventions, and certification of new data products.
Lead the triage and remediation of platform security or data incidents.
Build visibility into cloud and compute cost drivers; drive FinOps practices to optimize spend across environments.
Design repeatable onboarding processes for new tools, analysts, and integrations.
Manage vendor relationships, procurement processes and commercial contract negotiations, ensuring legal and compliance requirements are met.
Provide technical oversight of 3rd party supplier partnerships.
Lead platform modernization and migration programs, including planning, sequencing, and risk management for large-scale technology transitions.
Stay up to date with emerging technologies and industry trends, assessing their potential impact and benefit to the overall business strategy, particularly AI/agentic capabilities and data infrastructure innovations.