Data Engineer (m/f)
You are inspired by converting data into actual value? You are able to set up an efficient data architecture enabling tailored data products? You can guide customers on their way to becoming data-driven by optimizing their data landscape? You’re ambitious
Data Engineer with a strong technical background and the ability to build reliable and efficient data platforms.
Data is the core essence for all AI based business models, products and services. However, getting the most out of data is not an easy task. And it all begins with knowing how to efficiently work with data – from collection via transformation to storage. A performant yet reliable setup requires talent and know-how in state-of-the-art data technologies and tools. Team players with the ability to work closely with related data & AI experts as well as domain experts from various backgrounds to a common goal can excel. If this is you and you are keen to shape the future with bringing AI-based products and services into a variety of industries, then what are you still waiting for?
- Design and implement reliable (big) data storage solutions (on-premises or Cloud-based)
- Design and set up efficient data (transformation) pipelines.
- Monitor health of data storage and transformation and optimize accordingly.
- Advise on and implement best practices for data security and data privacy.
- Keeping up to date with state-of-the-art data technologies, tools and relevant trends
- Researching the feasibility of data-enabled use cases.
- Identifying data sources and data gaps and supporting in establishing a data strategy
- Collaborating with data scientists, machine learning engineers and other stakeholders in continuously optimizing the product delivery method.
- At least 3 years of data engineering experience concepting, designing and implementing data storage and transformation, ideally in the context of data science and machine learning.
- Excellent know-how on data storage solutions (structured and unstructured, on-premises and Cloud-based) and track record in their setup with strong consideration of data security
- Excellent understanding of data processing in stream and batch (e.g., PySpark, Kafka)
- Hands on experience with data engineering in Cloud environment
- Profound technical skills acquired through academic studies (e.g., computer science) or comparable work experience.
- Experience and interest in data analytics and data visualization (e.g., Tableau, Power BI) is a plus
- Strong analytical & problem-solving skills
- Team player with hands-on mentality focusing on customer satisfaction.
- Demonstrated commitment to continuously learn about data engineering.
- A new way of thinking and working that rapidly brings success to innovative ideas.
- Work in an agile team of experts who enjoy sharing ideas and expertise.
- Open communication, flat hierarchy, plenty of individual responsibility.
- The opportunity of evolving rapidly by pushing transformative DS/ML products into industries.
- The gross monthly salary starts at 3.300 Euro (according to the collective agreement for data processing and information technology) and, depending on qualifications and experience, usually ranges around 3.900 Euro, in the case of special qualifications, we are also prepared to negotiate beyond that.
Digital transformation opens up new opportunities for many industries. To take advantage, it isn’t enough to come up with a good idea. It’s about introducing smarter digital products and services onto the market faster than the competition.
Sclable combines the expertise of a management consultancy with the creativity of a design agency and the competence of a technology company. We apply cutting edge approaches from Artificial Intelligence and Machine Learning. This enables new business ideas, products and services that would otherwise be impossible.
Since its launch in 2012 Sclable has been working on the interface between consultancy, technology and design. It has helped many prosperous companies and partners to achieve even greater success ever since. Companies like Umdasch Group Ventures, Doka, Palfinger, Nedschroef, Roland Berger and many more.