Senior Data Engineer Platform & Operations
IMMO Investment Technologies
- Developing our core data platform functionality to enable data professionals and product teams with easy access to relevant data, interfaces, and functionality for reliably processing, storing and publishing data.
- Creating technology solutions to ensure compliance with internal and external policies within the data platform.
- Implement processes and technology to generate relevant documentation and discoverability of data (glossary, data dictionary, data lineage, etc) to improve data literacy and governance across the organization.
- Collaborating with the tech leadership and especially architecture to understand and improve our system landscape and company-wide data architecture.
- Temporarily supporting projects and product teams with the appropriate data architecture and implementation of new functionality. Aid data scientists with development and deployment of their solutions.
- Identifying opportunities on how to use data, insights and analytics more powerfully to automate and optimise our processes and solutions.
- A good understanding of the different data needs of analytics and engineering teams and how they could be met. Ideally, you have already successfully supported analytics and/or engineering teams with data platform capabilities.
- You effectively enabled & trained others to work with the data tools and services you provided.
- You used or ideally managed message brokers (like Kafka) to share data updates across services and applications.
- You have a solid understanding of software design principles and DevOps.
- You have a solid understanding of distributed processing systems such as Apache spark or any other such tech.
- You have experience with Infrastructure as Code tools such as terraform or terragrunt. Ideally, you have production experience in AWS.
- You are a self-starter who is comfortable working autonomously and with teams located across our offices. You’re not afraid to get your hands dirty, prioritize your focus based on impact, and are able to own a project from start to finish
- Nice to have: Production experience with machine learning (MLOps) or containerised solutions (Docker/Kubernetes).
- You have a strong foundation in Python and SQL.