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Publicis Groupe

Runs advertising and digital transformation services

Vice President, Data Engineering - Data Enablement

Data EngineeringConfirmed live in the last 24 hours
Full-timeChicago, IL, USA$135.4k - $194.5k /yrIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field is preferred.
  • At least 12 years of progressive experience in data engineering, data architecture, software engineering, or related technical disciplines.
  • At least 5 years of experience leading and developing data engineering teams at the Director level or above.
  • Demonstrated experience designing and implementing large-scale enterprise data platforms and data products.
  • Deep understanding of data warehouse, data lake, ETL/ELT, data integration, and data modeling principles.
  • Strong experience with cloud-based data technologies, preferably AWS, Azure, and/or Google Cloud.
  • Experience working with large, complex datasets and high-volume data environments.
  • Demonstrated experience establishing enterprise data architecture, engineering standards, and technology roadmaps.
  • Experience integrating structured and unstructured data, APIs, real-time data, and batch data environments.
  • Strong understanding of data governance, data quality, security, privacy, and data lifecycle management.
  • Experience partnering with senior executives and translating complex technical concepts into clear business recommendations.
  • Ability to lead through influence and operate effectively in a complex, highly collaborative environment.
  • Strong technical understanding and experience with SQL and SQL Server; Python, Java, C#, or similar programming languages; ETL/ELT technologies; data warehouses and data lakes; AWS, Azure, and/or Google Cloud; Apache Spark and distributed data processing; REST APIs and data integration; JSON, XML, ORC, Avro, and Parquet; Tableau and Datorama; web analytics and digital marketing data; data modeling and enterprise data architecture; data quality, metadata, lineage, and governance technologies; and modern data platform and data engineering architectures.

Responsibilities

  • Define and implement the enterprise data engineering strategy and multi-year technology roadmap in alignment with PHM’s business and data strategy.
  • Establish scalable architecture for data warehouses, data lakes, data platforms, and data products supporting enterprise and client-facing needs.
  • Lead the evolution of cloud-based data infrastructure and engineering capabilities across AWS, Azure, Google Cloud, and related technologies.
  • Establish architectural standards for data integration, data modeling, ETL/ELT, APIs, real-time data, batch processing, and data delivery.
  • Drive the modernization and optimization of existing data platforms, processes, and technology investments.
  • Evaluate emerging technologies and find opportunities to leverage automation, artificial intelligence, machine learning, and other innovations to improve data engineering capabilities.
  • Oversee the development of high-performance data products and platforms supporting analytics, business intelligence, media performance, measurement, and activation.
  • Ensure data products are designed for scalability, reliability, accessibility, and performance.
  • Establish standards for data modeling, metadata management, data quality, lineage, security, and governance.
  • Guide the integration of structured and unstructured data from internal, external, digital, media, and client data sources.
  • Ensure data platforms can support real-time, on-demand, batch, and varying data delivery requirements.
  • Partner with analytics and business intelligence leadership to ensure data engineering capabilities effectively support enterprise reporting and decision-making.
  • Build, lead, and develop a data engineering organization with deep technical and business acumen.
  • Establish engineering best practices, development standards, documentation practices, and quality controls.
  • Provide technical leadership and mentorship to Directors, engineering managers, and senior technical talent.
  • Define organizational capabilities, team structures, and talent strategies needed to support PHM’s evolving data ecosystem.
  • Establish and monitor engineering performance metrics, service levels, and operational standards.
  • Partner with data governance, information security, legal, privacy, and technology teams to establish appropriate standards for data management and usage.
  • Champion enterprise-wide data quality, governance, security, privacy, and compliance practices.
  • Establish processes for data lineage, metadata management, access controls, retention, and data lifecycle management.
  • Ensure data platforms and products meet appropriate standards for reliability, availability, scalability, and security.
  • Drive proactive identification and resolution of data quality, platform, and engineering risks.
  • Serve as a senior strategic advisor on data engineering, technology, and data platform decisions.
  • Partner with executive leadership to translate business objectives into scalable data and technology strategies.
  • Collaborate with Data Science, Analytics, Business Intelligence, Media, Technology, and Product leaders to find opportunities for data-driven innovation.
  • Communicate complex technical concepts and strategic recommendations to executive and non-technical audiences.
  • Represent Data Engineering in senior leadership discussions, strategic planning, and technology investment decisions.
  • Build relationships with internal stakeholders, technology partners, vendors, and client-facing teams.
  • Identify opportunities to improve how PHM collects, manages, integrates, and activates data.
  • Lead modernization initiatives that improve engineering efficiency, data accessibility, and business value.
  • Assess emerging data technologies, cloud capabilities, artificial intelligence and machine learning applications, and industry trends to determine opportunities for PHM.
  • Promote automation and reusable data engineering capabilities across the organization.
  • Establish a culture of experimentation and continuous technological improvement.

Desired Qualifications

  • Experience within media, advertising, healthcare, health media, digital marketing, or another data-intensive industry.
  • Experience working with media performance, measurement, audience, web analytics, or digital marketing data.
  • Experience leading enterprise-scale data modernization or cloud transformation initiatives.
  • Experience developing data products that support business intelligence, analytics, measurement, or media activation.
  • Experience working in a highly matrixed organization with multiple business units, clients, and technology stakeholders.

About the Company

Publicis Groupe

Runs advertising and digital transformation services

Publicis Groupe runs advertising, media buying and digital transformation services for companies that want to reach consumers, coordinate campaigns and improve their business systems. Its agency network includes creative and media specialists, while Publicis Sapient builds and modernizes the technology behind clients' operations. Epsilon adds customer data and marketing technology that connect brands with audiences and measure campaign results. Clients pay for consulting, campaign creation and execution, with production and media costs billed through alongside the group's service work. Founded in 1926, Publicis Groupe is headquartered in Paris, France.

Company size
10,001+
Company stage
IPO
Headquarters
Paris, France
Founded
1926

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