About the Performance Marketing Team
We are launching a new cross functional team of software engineers, data engineers and data scientists to tackle the complex domain of performance marketing. We have ambitious plans around scaling our automated bidding, reporting and attribution systems, and we’re looking for an experienced motivated Lead Engineer to build this team and lead them to success.
What you’ll be working on
- Owning and evolving data pipelines responsible for modelling marketing costs and returns across numerous channels and platforms
- Build performance marketing data products in our Data Mesh
- Scaling the usage of our automated bid management, including improving internal configuration tooling
- Working closely with commercial stakeholders to refine our roadmap and vision for the performance marketing capabilities of our platform
- Working closely with the Data Engineering and Data Science teams and participating in architectural design discussions as they evolve their platforms
- Leading a team of talented engineers and data scientists, fostering their growth and ensuring delivery of high-quality solutions and operational excellence
Your skillset
- You are an experienced and motivated lead engineer who is excited about building products in cross functional teams to realise business outcomes
- You have extensive experience in data and analytical engineering tools and frameworks, such as Bigquery, Airflow, dbt, Spark, Monte Carlo and Looker
- You enjoy collaborating across engineering and commercial teams to achieve shared goals, sharing knowledge with others and levelling up your team
- You own applications end to end, from specification to coding, to deploying, running and monitoring in production with tools such as Prometheus and Loki
- You have experience working with cloud computing, such as GCP or AWS
- You have experience or keen interest in the performance marketing space, including tag management, bid optimisation, ETL processes, and building data products and reporting based on 3rd party and internal data.
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