385 days ago on emploi.epfl.ch

Senior Data Engineer

EPFL - Ecole Polytechnique Fédérale de Lausanne

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Senior Data Engineer

Senior Data Engineer

Description

EPFL and ETH Zurich are seeking enthusiastic and experienced candidates with a proven track record in software engineering and product innovation on large-scale distributed platforms, services and applications to staff up their upcoming national R&D center for data science.

In this role, you will be contributing to the design and development of the center’s Insights-as-a-Service platform, a hosted one-stop-shop for accessing, exchanging and exploring possibly anonymized data at scale, and for building and deploying data science workflows.

Specifically, you will:

  • Design and build data ingestion and integration pipelines for large volumes of temporal data from different sources
  • Design and build very large data management systems
  • Liaise with data providers and data scientists to gather requirements and extend the center’s database management systems
  • Design and build web based APIs to facilitate easy access to data

Candidates are expected to possess deep hands-on experience with systems for large-scale distributed data processing. The ideal candidate has extensive background in Big Data technologies (minimally, Kafka, Hadoop, Spark), and with building applications at scale.

Requirements

You

  • Have a MSc in Computer Science, Electrical Engineering or related disciplines. Ph.D. degree is a plus
  • Have advanced Java, Scala or Python programming skills. Experience with real-world data is a plus
  • Have advanced data management skills, including knowledge of data curation, data governance and data stewardship
  • Have hands-on experience with data manipulation using SparkSQL, Hive, HBase, Phoenix, Solr or similar using a leading Apache Hadoop distribution. Understanding of file formats tradeoffs such as Parquet, ORC, or Avro is highly preferable
  • Have solid foundations in data structures, algorithms and design patterns
  • Are passionate about building out large-scale distributed systems in the cloud to process massive amounts of data
  • Seek out opportunities to engage and contribute to the open source community
  • Work well in a cross-functional environment and excel in communicating with your peers
  • Have excellent command of the English language, both verbal and written. Good working knowledge of French or German is highly desirable.

Benefits

  • A stimulating, startup-like, cross-disciplinary environment in a leading university
  • Opportunities for turning academic research into impactful solutions
  • Excellent ties to research groups worldwide, both academic and industrial
  • Access to state-of-the-art infrastructure and resources

 

About Us

The Swiss Data Science Center (SDSC, datascience.ch ) is a national center between EPFL and ETH Zurich, whose mission is to accelerate the use of data science and machine learning techniques broadly within academic disciplines of the ETH Domain and the Swiss academic community at large. It aims to federate data providers, data and computer scientists, and subject-matter experts around a cutting-edge analytics platform offering domain-specific “Insights-as-a-Service” while addressing security and privacy issues inherent to the field of data science. The SDSC will be composed of a large multi-disciplinary team of data & computer scientists and experts in relevant domains, distributed between our offices in Lausanne and Zurich. The unique synergy that the center will enable among the institutions of the ETH Domain and between academic and industrial stakeholders in both data science and across carefully selected domains is expected to foster scientific breakthroughs with significant societal impact.

 

Activity rate: Full-time or part-time

Start date:  To be discussed

 

Procedure for applications:

Candidates should submit their application online at https://datascience.ch/job-openings/

 

Contact:

For further information, please contact Dr. Olivier Verscheure (olivier.verscheure@epfl.ch)