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Publicis Groupe

Runs advertising and digital transformation services

Data Engineering Manager

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeIrving, TX, USA$105k - $195k /yrIn-person

About the Job

Requirements

  • At least 6 years of progressive experience in information technology, including at least 5 years in a dedicated engineering role focused on data, analytics, and artificial intelligence or machine-learning initiatives.
  • Extensive experience designing and developing identity spines or graphs in paid and owned audience spaces.
  • Demonstrable expertise in solution architecture design, including creating architectural diagrams, design documents, and technical specifications for complex systems.
  • Deep hands-on experience with Databricks and Snowflake, including data lakehouse patterns, SQL warehousing, and MLflow.
  • Extensive experience designing and implementing solutions on public cloud platforms, with proficiency in AWS (including Q, S3, EC2, Lambda, Glue, SageMaker, and RDS) and/or Azure (including Data Lake, Data Factory, Synapse Analytics, Azure ML, and Cosmos DB).
  • A proven track record designing and optimizing robust data pipelines using integration patterns such as ETL/ELT and streaming, and related tools.
  • Strong Python programming skills for data engineering, scripting, and automation.
  • Expert-level proficiency in SQL for data manipulation, querying, and optimization.
  • A solid understanding of artificial intelligence and machine learning concepts, including the model development lifecycle, MLOps principles, and integrating machine-learning models into production systems.
  • Experience with integration patterns and technologies, including APIs, message queues, and event-driven architectures.
  • Ability to communicate and present complex technical concepts to technical and non-technical audiences.

Responsibilities

  • Participate in end-to-end design of complex, scalable, fault-tolerant data and artificial-intelligence solutions aligned with business strategy, enterprise architecture standards, and industry guidelines.
  • Deliver CI/CD and DevOps capabilities in a data environment.
  • Assess existing systems and proposed architectures to identify gaps, risks, and opportunities for improvement and modernization.
  • Champion and design a data mesh architecture that enables high-quality, discoverable, reusable data products with decentralized ownership and consumption.
  • Define pipelines integrating artificial-intelligence and machine-learning models into operational systems, supporting model training, inference, and monitoring with robust data.
  • Design and optimize solutions primarily in AWS and Azure, making strategic choices about platform services, infrastructure, security, and cost efficiency.
  • Drive adoption and optimal use of Databricks for data engineering, machine learning, and analytics, and/or Snowflake for cloud data warehousing.
  • Design and oversee robust, automated, observable batch, streaming, and real-time data pipelines integrating diverse sources.
  • Architect and guide integration of new and existing systems, applications, and third-party services, defining data flows, API design, and security protocols.
  • Provide technical leadership, guidance, and mentorship to engineering teams, fostering innovation, excellence, and continuous improvement.
  • Collaborate with product owners, business analysts, data scientists, and senior leadership to gather requirements, present architectural options, and gain consensus.
  • Evaluate data, artificial-intelligence, and cloud technologies, tools, and methodologies, recommend strategic investments, and foster innovation.
  • Ensure architectural designs incorporate security measures, data governance, and compliance with relevant regulations, including GDPR, HIPAA, and industry-specific standards.
  • Design and maintain data-platform roadmaps and data structures supporting business and technology objectives.
  • Translate complex business requirements into high-performance technical solutions and shape the architectural vision and technical roadmap for data and artificial-intelligence initiatives.

Desired Qualifications

  • Experience with Java, particularly for enterprise application integration or backend services.
  • Databricks platform certifications, such as Data Engineer Professional or Gen AI Engineer Professional.
  • Experience with Kafka, Spark, or Flink.
  • Familiarity with containerization using Docker or Kubernetes and CI/CD practices.
  • Experience building reusable feature pipelines.
  • Experience ensuring training/serving parity.
  • Experience managing embedded pipelines.
  • Hands-on experience with vector database integrations.
  • Experience with Adobe products, including AEP, AJO, CJA, Campaign, Audience Manager, or Analytics; expertise is not required.
  • Experience with Salesforce Marketing Cloud or Data Cloud; expertise is not required.
  • Experience with Microsoft Power BI or Tableau; expertise is not required.

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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