Novelis, headquartered in Atlanta, USA, is the leading producer of flat-rolled aluminium products and the world's largest recycler of aluminium with a recorded US$ 11.2 billion in revenue (FY 2020). The company with its approx. 15'000 employees and 33 operations in 9 countries is driven by its purpose to shape a sustainable world together. Customers include some of the largest and best-known aerospace, automotive, beverage can, architecture and consumer electronics brands in the world.
Novelis Europe has approx. 6'000 employees in France, Germany, Italy, Switzerland and the UK. The European headquarters in Switzerland (Küsnacht ZH).
Novelis is looking for a
Data Engineer (m/f/d)
to join our Global Digital Team. He/she will aid in the optimization of operations by manipulating and aggregating the disparate operational and back office data sources into a format that is easily digestible by both data scientists and statistically adept colleagues. His/her core responsibility will be to combine large volumes of disparate complex data, conduct quality checks on the data, manipulate the data and ensure continuous access to a clean format of the operational data for data scientists and other stakeholders. In addition, he/she will also assist in developing the data pipeline to ensure ongoing data collection, consolidation, and management.
The working place of this position could be one of our German or Switzerland locations:
- Göttingen, Germany
- Koblenz, Germany
- Nachterstedt, Germany
- Plettenberg, Germany
- Sierre, Switzerland
- Design and Develop data ingestion pipelines and processes based on requirements in Python and PySpark
- Create error handing, exception management and data quality routines to expose the anomalies in the data
- Profile and analyze data to identify gaps and potential data quality issues
- Identifies relationships between disparate data sources
- Uses Python, Databricks and Spark to code the data Engineering routines
- Perform unit and integration testing
- Works with the group of data scientists and business SMEs to get the requirements and present the details in data.
- Designs and jointly develops the data architecture with data architect and ensures security and maintenance
- Explores suitable options, designs, and creates data pipeline (data lake / data warehouses) for specific analytical solutions
- Identifies gaps and implements solutions for data security, quality and automation of processes
- Builds data tools and products for effort automation and easy data accessibility
- Supports maintenance, bug fixing and performance analysis along data pipeline
- Diagnoses existing architecture and data maturity and identifies gaps
- Gather requirements, assess gaps and build roadmaps and architectures to help the analytics driven organization achieve its goals
- 3+ years of experience in data engineering using Python, PySpark and/or Spark
- Bachelor’s Degree in Computer Science, Engineering, and/or background in Mathematic and Statistics; Master’s or other advanced degree a plus
- Experience on Big Data platforms (e.g. Hadoop, Map/Reduce, Spark, HBase, HDInsight, Data Bricks, Hive) and with programming languages like UNIX shell scripting, Python etc.
- Has used SQL, PL/SQL or T-SQL with RDBMSs like Teradata, MS SQL Server, Oracle etc in production environments
- Experience with reporting and BI packages e.g. PowerBI, Tableau, SAP BO etc.
- Strong critical thinking and problem solving skills
- Success at working on cross-functional teams to meet a common goal
- Self-starter with a high sense of urgency
- An international working environment with a cooperative culture, room to take additional responsibilities and an open communication through all levels
- An attractive salary with an additional bonus program
- Our competitive company pension scheme and a variety of other benefits
- Internal and external development programs to support your career aspirations