Description:
The Data Platform team is going through a period of transformation, with the goal of ensuring that our foundations for data processing are scalable and ready for a future where we handle data from hundreds of millions of users.
We are looking for a Senior Data Engineer to help drive this transformation, by increasing our platforms' performance, streamlining processes and continuing to ensure that we respect our users' privacy. You’ll have the opportunity to influence team culture, and work with your team members on both strategy and execution.
- Design and build data platforms, endpoints and pipelines that meet business requirements and enable stakeholders to make more data-driven decisions, without losing track of technical quality and maintainability
- Actively collaborate with teams across all of eyeo (like browser extension developers, data analysts and legal counsels) to design data collection systems that are compliant with regulations and respect user privacy
- Manage software from proof-on-concept to deployment, to operation, and finally deprecation; and manage data through ingestion, access, schema changes and deletion
- Improve both our software and data lifecycle processes
- Implement strategies to ensure that data is accurate, complete, timely and consistent
- Identify, design and implement process improvements: automating manual processes, simplifying collaboration with data analysts, etc
- Contribute to ongoing management of our platforms, including performance monitoring, troubleshooting and resolution of technical issues
- Be a multiplier in your team, encouraging debate, and helping to create an environment that fosters learning and growth
What You Bring To The Table
- Experience translating data strategy into scalable, fault-tolerant architectures
- Familiarity with different approaches to data architecture: warehouse, lake, mesh, batch vs streaming, ETL vs ELT, etc., and how they can be leveraged in different use cases
- Experience in Python and common data libraries and platforms such as Airflow, Pandas, PySpark, etc
- Experience with cloud services (ideally Google Cloud), including managing infrastructure with Terraform
- Expertise with advanced SQL queries and query optimization, ideally in BigQuery
- Passion about introducing engineering best practices, for instance to ensure testability, data quality and completeness, etc
- Excellent communication and collaboration skills, both with engineers and non-technical stakeholders