Compliance & Data Research Lead (Remote)

The Role 

As a Data Engineering Manager youll lead a team of engineers responsible for the design delivery and reliability of our data platform. 

You will guide a squad of 1015 engineers (34 direct reports) in building scalable observable and well-modeled data systems that power marketing revenue and analytics decisions across the company. 

This role combines technical depth with delivery leadership: youll drive design and best practices mentor engineers and partner with Program Management to ensure predictable high-quality releases. Youll collaborate across Analytics RevOps Data Ops and Product to turn business problems into performant future-ready engineering solutions. 

What Youll Do 

Commercial Impact 

• You will be crucial to driving revenue growth for the business through flexible and scalable data ingestion creation of microservices that can be used for decisioning and driving forward data practices. 

Team Leadership and Delivery 

• Lead mentor and develop a high-performing data engineering squads delivering production-grade pipelines and services. 

• Set technical and operational standards for quality documentation and reliability. 

• Partner with Program Management to plan prioritise and track delivery against sprint goals. 

• Foster a culture of ownership engineering excellence and continuous improvement. 

Architecture and Technical Design 

• Contribute to architectural reviews and solution design in collaboration with the Director of Data Engineering. 

• Ensure scalable modular pipeline design and adherence to strong data modeling principles in dbt and BigQuery. 

• Lead the transition from monolithic pipelines to microservice-based data workflows that are reusable and observable. 

• Champion consistency and semantic alignment across datasets and layers (Bronze Silver Gold). 

Platform Ownership 

• Oversee implementation and optimisation of workflows in GCP (BigQuery Cloud Composer Cloud Functions Vertex AI etc.). 

• Drive observability cost efficiency and data quality through monitoring and alerting standards. 

• Lead adoption of best practices in version control CI/CD testing and automated QA. 

• Evaluate new tools and frameworks that enhance scalability and engineering productivity. 

Cross-Functional Collaboration 

• Translate stakeholder requirements into robust technical designs that align with marketing analytics and revenue goals. 

• Partner closely with Analytics BI Ops and RevOps to deliver reliable data foundations for attribution 1PD activation and performance optimisation. 

• Communicate progress risks and dependencies clearly to technical and non-technical partners. 

Technical Standards and Mentorship 

• Review designs pull requests and pipelines for scalability maintainability and efficiency. 

• Coach engineers on clean coding practices modular design and testing discipline. 

• Embed best practices for documentation schema governance and dependency management. 

• Model engineering-first leadership balancing technical depth with empathy clarity and decisiveness. 

What Youll Bring 

Minimum Qualifications 

• 10 years of total experience in data or software engineering including 2 years leading teams. 

• Deep expertise in SQL Python and modern ELT tools (dbt Airflow/Composer). 

• Strong understanding of data modeling orchestration and optimisation in GCP (BigQuery GCS Pub/Sub). 

• Demonstrated experience building or scaling data pipelines for marketing attribution or monetisation. 

• Proven ability to lead delivery within agile sprints and coordinate with cross-functional stakeholders. 

• Excellent communication prioritisation and leadership skills in distributed teams. 

Nice to Have 

• Experience transitioning large-scale architectures to microservices or event-driven designs. 

• Familiarity with CI/CD pipelines observability frameworks and cost optimisation in cloud environments. 

• Exposure to machine-learning pipelines model serving or real-time scoring. 

• Background working with marketing or product analytics data sources (Google Ads Meta GA4 Taboola etc.). 

What Success Looks Like 

• Fully operational microservice-based data workflows with strong observability and documentation. 

• High stakeholder trust and on-time delivery of revenue attribution and ingestion initiatives. 

• Consistent semantic data models powering analytics and attribution across the business. 

• A self-sufficient empowered engineering team operating with speed clarity and quality. 

• Data platform seen as a reliable scalable foundation for 1PD strategy and future AI use cases. 

Why Join Us 

• Remote-first collaborative culture with flexible working hours. 

• Opportunity to shape the engineering foundations of a world-class data organisation. 

• Exposure to complex high-impact problems across marketing revenue and product. 

• Monthly long weekends wellness stipend and generous parental leave. 

• Work with global leaders in data marketing and engineering building systems that drive real business growth. 

Remote Work :

Yes

Employment Type :

Full-time