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WPP Media

AI-native global media services network

Data Management and BI Manager - GOC

Data EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • Multiple years of hands-on professional data engineering experience in production; 3 or more years of relevant experience is strongly preferred. Experience must include personally building or maintaining production data pipelines, beyond academic projects or reporting-only responsibilities.
  • Demonstrated ownership of end-to-end ETL/ELT pipelines and ability to explain personally implemented or maintained source systems, storage layers, transformations, target datasets, orchestration, and monitoring.
  • Strong hands-on SQL skills, including independently writing and troubleshooting queries using joins, aggregations, common table expressions, and window functions, and applying SQL to data validation, duplicate detection, and reconciliation.
  • Practical production experience with cloud data pipelines. Azure Data Factory, Azure Data Lake Storage, and Azure SQL are the target stack; candidates with strong Google Cloud Platform data engineering experience may also be considered if they demonstrate solid ETL/ELT fundamentals and can translate pipeline patterns across cloud platforms.
  • Relevant hands-on Databricks experience, including working with data workloads and distributed transformations.
  • Ability to independently write Python for data automation, API extraction, and data processing, supported by concrete examples of professional implementation.
  • Direct experience monitoring production pipelines, investigating failures, performing root-cause analysis, and implementing durable fixes.
  • Practical understanding of safe development-to-production delivery, including version control, testing, environment configuration, deployment practices, and rollback considerations.
  • Ability to clearly explain technical decisions, personal contributions, troubleshooting approaches, and production outcomes.
  • Candidates must reside in Mexico or Colombia and be legally authorized to work in the country where they reside.
  • Candidates must complete a live SQL coding assessment and discuss practical pipeline design, Python usage, and production reliability; they must be prepared to write, explain, and troubleshoot their own queries without external artificial intelligence or code-generation assistance.

Responsibilities

  • Design, develop, and optimize enterprise ETL/ELT pipelines using Azure Data Factory, Azure Data Lake Storage, and serverless technologies, ensuring scalability, security, and reliability.
  • Build and optimize complex Azure T-SQL solutions, including query tuning, partitioning, and indexing, to support advanced analytics models and real-time data processing.
  • Develop automation frameworks with Python and API orchestration to streamline the data lifecycle and improve operational efficiency.
  • Own production pipeline reliability by performing root-cause analysis, resolving critical incidents, and implementing long-term stability measures.
  • Define and enforce coding and architectural standards through code reviews and technical audits, while mentoring engineers and improving delivery quality.
  • Maintain technical documentation, data lineage, governance, and automated continuous integration and continuous deployment practices across data assets.
  • Partner with United States onshore leadership, analytics teams, and media teams to translate business requirements into scalable, high-performance technical solutions.
  • Lead end-to-end pipeline architecture and modernization initiatives involving Azure Databricks, dbt, and advanced DevOps practices.
  • Monitor service-level agreements, mitigate technical risks, and support data security and compliance requirements.

Desired Qualifications

  • Advanced T-SQL performance tuning, including indexing, partitioning, and execution-plan analysis.
  • Delta Lake optimization, Spark performance tuning, and Databricks job orchestration.
  • Building reusable Python automation frameworks, including testing, packaging, concurrency, and robust retry and backoff handling.
  • Ownership of service-level agreements and objectives, observability, data lineage, and incident-prevention practices.
  • Experience with Terraform or other infrastructure-as-code tools, Azure DevOps, dbt testing, and data governance practices.
  • Experience mentoring engineers, making architectural decisions, or leading platform modernization initiatives.

About the Company

WPP Media

AI-native global media services network

WPP Media is a global media services arm that manages more than $60 billion in annual advertising investments for leading brands. It operates across a network of established agencies (Mindshare, Wavemaker, EssenceMediacom) and combines media planning, data, production, and commerce through its proprietary WPP Open platform. Its Open Intelligence data model uses real-time behavioral signals to drive predictive, faster, and smarter marketing campaigns. The company positions itself as an AI-native media collective, consolidating capabilities under a single technology stack to improve efficiency and scale for advertisers. Its goal is to help clients buy and optimize media more effectively by leveraging integrated data, advanced analytics, and automated execution at scale.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
New York City, New York
Founded
2003

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