Data Engineer

At VML, we are architects of connected brands and experiences for a changing world. We believe in the powerful synergy of creativity, technology, data, and culture to build brands that not only grow faster but also resonate deeply and personally with their customers. We are experts in marketing transformation, marketing science, and advanced marketing automation and personalization, relentlessly pushing the boundaries of what's possible.

We power over 350 million personalized experiences between brands and their customers every day. We achieve this by applying our deep expertise, leveraging strategic partnerships with the biggest technology platforms in the world, and by harnessing cutting-edge advancements in Artificial Intelligence, Machine Learning, and Large Language Models. We work closely with our clients as true growth partners, helping them not just achieve their goals but redefine them for the future. This particular opportunity offers the chance to work directly with one of our tier-one automotive clients, a global brand powerhouse, helping shape their digital future.

Our global team of 4,000+ data specialists serves more than 150 markets across the globe. We operate with unwavering integrity, a profound respect for data privacy, and complete transparency. We champion new ideas and diverse perspectives, fostering a culture of creative bravery, open listening, positivity, and collective strength in all that we do. We are constantly evolving, empowering our clients to stay ahead in a rapidly accelerating digital landscape. Please note that UK working hours will be required for this role.

Overview

The Data Engineer, Marketing & Analytics, is a key technical contributor responsible for designing, building, and maintaining 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 ensuring high-quality, reliable, and accessible data for analysis, reporting, and advanced analytical initiatives, including feeding platforms like Amplitude.

You will leverage a modern data stack including Google Cloud Platform (GCP), Matillion for ETL/ELT, Snowflake as our cloud data warehouse, and Rudderstack for customer data ingestion. Your work will directly enable our analytics and data science teams to derive critical insights, fuel AI/ML applications, and provide robust data to product analytics platforms like Amplitude. Beyond pipeline development, you will also be responsible for monitoring, troubleshooting, and optimizing data workflows. This position requires strong engineering principles, a meticulous approach to data quality, and a collaborative spirit to work with cross-functional teams.

Responsibilities:

As a Data Engineer, your duties will include, but will not be limited to, the following:

• Data Pipeline Development: Design, develop, and implement scalable and reliable ETL/ELT pipelines using Matillion and GCP services (e.g., Cloud Functions, Cloud Storage, Big Query, Composer/Airflow) to ingest, transform, and load digital and media data into Snowflake.
• Data Ingestion & Integration: Configure and manage data streams from various sources, including customer data platforms like Rudder stack, APIs (e.g., ad platforms, analytics tools), and other raw data feeds. Understand and integrate data from advanced omnichannel tagging and data collection systems, ensuring data readiness for tools like Amplitude.
• Data Transformation & Modeling: Develop complex SQL transformations within Snowflake to clean, enrich, and model data for optimal performance and usability by reporting tools (e.g., Tableau, Amplitude) and analytical applications. Design and implement data schemas (star, snowflake, data vault) to support business requirements.
• Infrastructure Management: Monitor, maintain, and optimize the performance, security, and cost-efficiency of our data infrastructure components across GCP and Snowflake.
• Quality Assurance & Monitoring: Implement robust data quality checks, validation rules, and automated monitoring solutions for all data pipelines to ensure accuracy, completeness, and timeliness of data delivered to various platforms, including Amplitude. Troubleshoot and resolve data discrepancies and pipeline failures promptly.
• Reporting & Visualization Support: Collaborate with analytics specialists and data visualization experts (e.g., those using Tableau and Amplitude) to ensure data models meet their reporting needs and are optimized for query performance.
• Documentation & Governance: Create and maintain comprehensive documentation for data pipelines, data models, schemas, and data dictionaries. Adhere to data governance best practices, including data privacy (GDPR, CCPA) and security standards.
• Collaboration & Innovation: Work closely with data analysts, data scientists, product managers (who often use Amplitude), solution architects, and client teams to understand data requirements and translate them into technical solutions. Stay informed on emerging data engineering technologies, AI/ML data preparation techniques, and best practices.
• Automation: Automate routine data management tasks, monitoring, and deployments where possible using scripting languages like Python.

REQUIREMENTS

• Minimum 5 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 organization 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.

Technical & Development Expertise:

• Cloud Platforms: Proven experience with Google Cloud Platform (GCP), particularly BigQuery, Cloud Storage, Cloud Functions, and orchestration tools like Cloud Composer (Apache Airflow).
• Data Warehousing: Solid expertise in Snowflake including data loading, SQL querying, performance tuning, and schema design (star schema, snowflake schema).
• ETL/ELT Tools: Strong hands-on experience designing and building data pipelines with Matillion (or similar tools like Fivetran, Stitch).
• Customer Data Platforms (CDPs): Experience with Rudder stack for event collection, data routing, and destination management.
• Product Analytics Platf