DATA ENGINEER (MEDICAL PRODUCTS)

  • Altran Technologies
  • Basel, BS, Switzerland
  • 15/06/2020
Full time Data Science Data Engineering Big Data Statistics

Job Description

  • A permanent contract with the leader in innovation and high-tech engineering consulting
  • A multi-stage model with career opportunities through specialization prospects with over 250'000 consultants around the world and a Group revenue (Altran/CapGemini) of EUR. 17 Bn, the Altran Group is the undisputed global leader in Engineering and R&D services (ER&D)
  • In Switzerland, Altran employs more than 400 consultants and aims towards large growth with offices located in Zürich, Basel, Lausanne and Geneva.

Your role

We are looking for data engineers bringing expertise in two or more of the following areas:

  • Building reliable data pipelines using Spark / Python / R
  • Provisioning data / providing access, building REST/similar APIs back-ended by technologies such as PostgreSQL/ElasticSearch/S3/…
  • Clinical trial datasets (SDTM/ADAM/…)
  • Biological datasets (e.g. omics; DNA/RNA)
    • Design, create, test, and maintain optimal data pipeline architecture to ensure that it supports the requirements of the stakeholders
    • Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources
    • Develop data set processes for data modelling, mining, and production to deliver data
    • Delivery of clear, maintainable, and well-tested code in a timely manner
    • Identify, design, and implement internal process improvements; automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
    • Create data tools/scripts for data curators and data scientists as needed
    • Collaboration with scientists, data managers, and technology teams to document and leverage their understanding of the data
    • Actively participate in agile work practices
    • Adopt and improve on the strong engineering practices followed by technology teams
    • Analyse analytical blueprints to identify technical gaps and build best practices

Your profile

  • Computational/quantitative background; degree in a computational science (e.g. computer science, physics, engineering...),
  • Software engineering experience (versioning, Scrum, testing, collaboration good practices)
  • Some experience with Python for pipelines, engineering practices, … (e.g. Python + Spark; Dask, Snakemake, etc.)
  • Strong experience with Python for pipelines, engineering practices, (e.g. Python + Spark; Dask, Snakemake, etc.)
  • Some experience with R for data analysis (SparkR/sparklyr, tidyverse, mlr, ...),
  • Experience with computational environments for large-scale processing
  • (high-performance computing and/or Spark),
  • Analysis of clinical trial data, incl. understanding of data formats, processes, …