Senior Data Engineer

City: Basel
Country: Switzerland
Duration: 12 Months

Job purpose
Senior Data Engineer has the responsibility to design data pipeline architecture in a strong partnership with Product owner to fit with product roadmap needs.
He plays a role as a mentor for the Data Engineer community to ensure that best practices and processes are met.
Responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and transformations.

Major Accountabilities
• Responsible for defining how to develop the pipeline and his overall quality
• Help the team in building new and relevant data engineer features for enhancing the pipeline according to the roadmap.
• Plays a mentorship role to ensure the optimal application of best practices, coding conventions over the pipeline and assist data engineer in their duties upon request
• Helps the team to achieve and surpass product and program goals
• Provides technical guidance and direction as well as contributing hands-on to pipeline development
• Acts as an evangelist and guiding practitioner of agile and devops practices

Ideal Background
- Bachelor’s/Master's degree in Computer Science, Applied Mathematics, Engineering, or any other technology related field; equivalent of the same in working experience may also be accepted
Responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and transformations
Strong troubleshooting and problem solving skills
Experience building large-scale software systems and implementation of creative solutions to difficult computational problems (with emphasis on performance and near real-time data analytics)
Senior level data engineering (e.g. ETL) experience
Databricks or Spark experience
Proficient in Python, R or Scala
Experience with AWS / Azure cloud technologies and stack
Experience building big data applications and pipelines using Spark
Strong knowledge in DevOps, coding conventions and best practices for User Acceptance Test
Self-motivated, curious, proactive and accountable
Solid communication skills

Other specific requirements could be:
Experience in medical imaging solutions
Understanding of data42 data capabilities and tools
Understanding of images storage best practices
Technical ability to configure images systems to load and transfer files
Knowledge of medical image formats and metadata
Work closely with data scientists to solve technical issues in building analytical blueprints in ML, DL, and genomic sequence analysis
Understanding of ML/DL and imaging processing in big data computing engine (e.g. Spark)
Familiarity with performance tuning skills (Spark, Data I/O);good knowledge about the internals of Spark and other components in Hadoop ecosystem (HDFS, Hive)