Senior Data Engineer (remote from EU)
PriceHubble is a PropTech company with over 200 employees, set to radically improve the understanding and transparency of real estate markets based on data-supported insights. We aggregate and analyze a wide variety of large scale datasets, and apply state-of-the-art machine learning to generate high-quality valuations and predictive analytics for the real estate market. We are headquartered in Zürich, with offices in Berlin, Hamburg, Paris, Vienna, Prague, and Tokyo. We have a startup environment, low bureaucracy, an international team and business, and are backed by world-class investors.
You will be part of the Data Products team, responsible for building the large scale data transformation infrastructure and engineering that delivers several of the team’s data products.
As a Data Engineer, you will have a key role in helping to design and deliver efficient and scalable data products. These products will directly integrate in our customer workflows as well as support key functions of the applications we offer them, and you will have a direct hand in ensuring they are trustworthy, versatile, and deliver value to our customers.
You have the technical expertise to contribute to the product and maintain optimal delivery efficiency. You are curious to deeply understand the impact of the product in the organization and the value it delivers to PriceHubble clients and the real-estate industry.
You will strive at PriceHubble and in the Data practice if you have great empathy and team mindset, you value elegant and highly efficient engineering, and you derive great satisfaction from delivering very reliable and usable systems .
Your daily activities
- Define and deliver datasets that will act as the source-of-truth for PriceHubble’s processes and the activities of PriceHubble’s customers
- Scale and optimize data pipelines and data management systems to deliver those data products
- Track, monitor and improve the performance of these products, and optimize their trustworthiness for their use cases
- Leverage the cutting edge of the industry’s best practices and technology in data design and management to continuously improve the quality and efficiency of our data products
- Participate in improving and expanding the teams’ data and engineering standards, and support peers and more junior engineers on their application
- You enjoy working on a wide range of technical domains and use cases, in an international and multi disciplinary team.
- You are passionate about learning new things and transferring this knowledge to others.
- You are an empathetic team player and speak your mind, you measure success by what is accomplished and how others have been enabled by your work.
- BSc or MSc in computer science or related fields.
- 3+ years practice of agile methodologies and devops methods.
- 3+ years of experience in the Python data engineering ecosystem.
- Experience working with public cloud platforms (AWS, Azure or GCP).
- Extensive experience with data systems and microservices in the cloud, at scale (K8s, Kubeflow, Dataproc, Airflow, Spark…).
- Excellent skills in object-oriented programming, data structures and algorithms.
- Excellent skills designing distributed service architectures in a cloud environment.
- Structured and empathetic communicator, able to mentor other engineers and data scientists.
- Strong oral, written and presentation skills with ability to explain complex concepts clearly to a variety of audiences.
* We are interested in every qualified candidate who is eligible to work in the European Union / UK but we are not able to sponsor visas.
Join an ambitious and hungry team and enjoy the following benefits:
💰 Competitive salary because we always want to attract the best talents.
📘 Learning & Development program - We want you to feel happy, confident about improving your skills, experience level as well as your personal development success.
🏢 Very well-located offices with a great remote work policy and the possibility to work from different places.
🕓 Flexible working hours and work life balance.