The Senior Data Engineer, Marketing & Analytics, is a technical leader and architect responsible for designing, building, and owning robust data pipelines and infrastructure that power VML's digital and media reporting and product analytics for our tier-one clients. This role focuses on defining data strategy, ensuring high-quality, reliable, and accessible data for complex analysis, advanced reporting, and critical analytical initiatives, including feeding platforms like Amplitude. You will be instrumental in laying the data foundation that fuels AI/ML applications and provides strategic insights.

You will leverage and evolve a modern data stack including Google Cloud Platform (GCP), Matillion for advanced ETL/ELT orchestration, Snowflake as our cloud data warehouse, and Rudderstack for customer data ingestion and event streaming. Your work will directly empower our analytics and data science teams to derive critical insights, fuel AI/ML applications, and provide robust data to product analytics platforms like Amplitude. This role demands end-to-end ownership, strategic technical guidance, and the ability to mentor junior engineers, alongside a deep understanding of data engineering principles, meticulous attention to data quality, and a collaborative spirit to drive data initiatives across cross-functional and client teams.

As a Senior Data Engineer within the VML EMEA Enablement Team, your duties will include, but will not be limited to, the following:

• Data Architecture & Strategy: Lead the design and architecture of scalable, resilient, and performant data pipelines and data infrastructure solutions on GCP and Snowflake. Contribute to defining the data engineering roadmap, evaluating new technologies, and establishing best practices.
• Advanced Data Pipeline Development: Lead the development and implementation of complex and high-volume ETL/ELT pipelines using Matillion and advanced GCP services (e.g., Dataflow, Dataproc, Pub/Sub, Cloud Functions, BigQuery, Composer/Airflow) to ingest, transform, and load digital and media data into Snowflake. Drive automation and optimization of these pipelines for efficiency and reliability.
• Complex Data Ingestion & Integration: Architect and manage sophisticated data streams from diverse sources, including customer data platforms like Rudderstack, numerous APIs (e.g., ad platforms, analytics tools), and other raw data feeds. Ensure seamless and high-fidelity data integration from advanced omnichannel tagging and data collection systems into downstream systems like Amplitude.
• Data Transformation & Modeling Mastery: Define, design, and implement advanced SQL transformations and complex data models within Snowflake (e.g., dimensional modeling, data vault, wide table designs) to clean, enrich, and prepare data for optimal performance and usability by reporting tools (e.g., Tableau, Amplitude) and sophisticated analytical/AI applications.
• Infrastructure Management & Optimisation: Oversee, optimise, and secure the performance, reliability, scalability, and cost-efficiency of our data infrastructure components across GCP and Snowflake. Implement robust monitoring, alerting, and incident response solutions.
• Data Quality, Governance & Security Leadership: Establish and enforce robust data quality frameworks, validation rules, and automated monitoring solutions for all data pipelines, ensuring accuracy, completeness, and timeliness of data delivered to various platforms, including Amplitude. Drive compliance with data privacy regulations (GDPR, CCPA) and security best practices within the data architecture.
• Strategic Reporting & Visualisation Support: Partner closely with analytics specialists, data scientists, and data visualisation experts (e.g., those using Tableau and Amplitude) to define data requirements, optimize data models for query performance, and ensure the delivery of strategic insights.
• Mentorship & Technical Guidance: Provide technical leadership, guidance, and mentorship to junior data engineers, fostering a culture of continuous learning, knowledge sharing, and engineering excellence. Conduct thorough code reviews and ensure adherence to best practices.
• Collaboration & Innovation: Act as a subject matter expert and partner with data analysts, data scientists, product managers (who extensively use Amplitude), solution architects, and client teams to translate complex business requirements into robust technical data solutions. Proactively research, evaluate, and advocate for emerging data engineering technologies, AI/ML data preparation techniques, and industry best practices.
• Automation & CI/CD: Drive automation of data management tasks, monitoring, and implement Continuous Integration/Continuous Deployment (CI/CD) practices for data pipelines and infrastructure.

• Minimum 7 years’ engineering and development experience
• Strong Client-facing skills – responsive, results-driven, dedicated to customer support, and adept at consulting on complex technical and strategic data challenges.
• Strong attention to detail, excellent organisation skills, and ability to work independently and manage multiple projects/responsibilities and small teams in a fast-paced environment.
• Exposure to enterprise-level clients and understanding of complex web/app ecosystems, privacy regulations (GDPR, CCPA), and best practices for data governance.
• In-depth knowledge and understanding of various client websites, mobile apps, their business models, and online marketing/product strategy.

• Cloud Platforms: Deep expertise with Google Cloud Platform (GCP), particularly BigQuery, Cloud Storage, Cloud Functions, Pub/Sub, Dataflow/Dataproc, and orchestration tools like Cloud Composer (Apache Airflow).
• Data Warehousing: Mastery in Snowflake including advanced data loading strategies, complex SQL querying, extensive performance tuning, and designing intricate schema architectures (star schema, snowflake schema, data vault).
• ETL/ELT Tools: Expert-level, hands-on experience designing, developing, and managing complex and high-volume data pipelines with Matillion (or similar enterprise-grade ETL tools like Fivetran, Stitch, Talend, Informatica).
• Customer Data Platforms (CDPs): Extensive experience with Rudderstack (or Segment) for event collection, transformation, data routing, and destination management, understanding its role in the modern data stack.
• Product Analytics Platforms: Proven experience integrating data with, and optimizing data for, Amplitude (or similar leading product analytics tools like Mixpanel, Pendo). In-depth understanding of Amplitude's event taxonomy and user properties.
• Programming & Scripting: Advanced proficiency in SQL for complex data manipulation, optimization, and transformation. Strong proficiency in Python for scripting, automation, API integrations, and potentially data processing frameworks.
• BI & Reporting: Demonstrated experience working closely with BI developers and analysts using tools like Tableau (or Looker Studio, Power BI), understanding their data needs and optimising data models for reporting performance.
• Data Collection & Integration: Expertise in integrating data from a wide variety of sources, including numerous APIs, SFTP, streaming data, and a deep understanding of event-driven data architectures, especially from advanced omnichannel tagging and data collection systems.
• Data Modeling: Extensive practical experience with various data modeling techniques for analytical databases and data warehouses, including dimensional modeling, data vault, and normalised/denormalised approaches.
• Version Control & DevOps: Strong proficiency with Git and experience implementing CI/CD pipelines for data engineering workflows.
• Beneficial: Experience with streaming data technologies (e.g., Kafka, Pub/Sub, Dataflow streaming), experience with containerization (Docker, Kubernetes), or knowledge of other cloud platforms (AWS, Azure).

• Marketing & Product Data: Strong understanding of digital marketing data (e.g., ad impressions, clicks, conversions), media reporting metrics, product usage data (e.g., events, user flows as seen in Amplitude), and customer journey data.
• Data Governance: Familiarity with data privacy regulations (GDPR, CCPA) and best practices for data security and compliance.
• Analytics Ecosystem: Understanding of how data engineering supports analytics, reporting, and machine learning initiatives across various platforms including Amplitude.

• Client Engagement: Demonstrated experience as a senior consultant, engaging directly with clients to gather requirements, present solutions, and manage expectations.
• Communication: Exceptional written and oral communication skills, capable of authoring complex technical specifications, blueprints, and proposals, and confidently leading technical discussions.
• Problem-Solving: Proven ability to work collaboratively as part of a team to solve complex problems in varied, fast-paced environments.
• Project Management Acumen: Experience working effectively within a project management office framework.
• Methodologies: Familiarity and experience with best practice development methodologies.
• Adaptability: Ability to instill confidence through maturity, expertise, and impeccable communications.

WPP Enterprise Solutions is committed to Employment Equity and transformation. In accordance with our Employment Equity objectives, preference may be given to candidates from designated groups.

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About WPP

WPP is the trusted growth partner for the world’s leading brands. With exceptional talent, trusted data and intelligence and world-class partnerships – all united by our agentic marketing platform, WPP Open – we help clients navigate change, capture opportunity and deliver transformational growth. For more information, visit WPP.com .