Beschreibung
Position: Sr. Data Engineer
Location: Zurich, Switzerland
Contract Duration: 12 Months + possible ext
About the role
Your main duties will be:
- Lead and support the building and maintenance of end-to-end, scalable and flexible data pipelines as the basis for sophisticated analytics and Business Intelligence solutions that allow us to analyse and measure multichannel customer journeys
- Understand, model, integrate and leverage data from different sources (eg ticket data, web data, unstructured text data) to enable the crew's data analytics experts to detect anomalies, calculate KPIs, predict volumes and satisfaction levels. Build in the automation and integration within the pipeline to enable plug and play data source integration, within technical and organizational context.
- Apply and further develop concepts and best practices for effective DataOps, driving efficient operationalization of analytics solution and reduce time to market end-to-end
- Act as the data steward for all stakeholders, pro-actively ensuring data consistency, readiness, completeness and detection of issues in all data pipelines using advanced concepts like statistical process control, machine learning, anomaly detection
- Ensure the information architecture is in line with enterprise standards and tools
- Help the team and stakeholders to understand and interpret data to derive actions and make decisions
- Coach the analytics team of 5 people with different profiles and ensure smooth collaboration among them, across locations as well as analytics and reporting counterparts from other teams
- Become an active member of analytics community.
About you:
- You love analytics and working with data!
- Senior practical software & data engineering skills in a Python, SQL/NoSQL and private cloud context
- A strong drive to deliver operationalized solutions that enable reporting and data visualisation
- Extensive Datamodelling skills and experience
- Good knowledge of algorithms and data structures, very good understanding in relational data bases and how to implement data pipelines pragmatically using available tools
- University degree in Computer Science, Data Science, Engineering, Statistics, Mathematics or comparable education
- 7+ years professional experience in data engineering, preferably applying DataOps best practices
- Proven problem-solving skills and attention to detail
- Highly motivated self-starter, pro-active, keen on learning and open to new ideas
- Although you love data & technology, you understand that data is a means to an end: You enjoy communicating with all stakeholders and you are a critical thinker by nature who likes to develop your own ideas in close collaboration with other team members and teams from other units
- Self-organised and have a good feeling of when you have just to inform, to consult, to involve or to ask others for approval
- Can walk in the shoes of senior stakeholders and have the ability to navigate ambiguity and take ownership, you perceive this as a positive challenge and a source of self-fulfilment, not as a stress-factor