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DevOps Engineer SQL Batch/Shell Scripting ETL SSIS SSRS Genève - Suiss

Posted on Jan 10, 2021 by McCabe & Barton

Genève, Switzerland
Immediate Start
Annual Salary

DevOps Engineer SQL Batch/Shell Scripting ETL SSIS SSRS Genève - Suisse Switzerland

We are looking for a DevOps engineer with SQL Batch/Shell Scripting ETL SSIS SSRS.

If you have python and/or machine learning this job is made for you!

We are looking for candidates in the Genève area and/or frontaliers.

We are looking for a DevOps Engineer with a focus on and a typical day might include any of the following:

  • Managing schedulers (Jenkins) to extract data from production databases
  • Batch, Shell Scripting to move data within the data warehouse
  • Overseeing log-files to ensure data reporting jobs (currently c.40 per month) are running smoothly
  • Designing new work intake pipeline with business and Data Science teams to deliver new data reports
  • Jointly, with Data Scientists, designing automated communication strategies for internal and external stakeholders

MUST be Competent with:

  • Understanding Data Scientists' requirements for organisation and accessing data
  • Batch and/or Shell Scripting
  • SQL Server database tasks such as backup, restore, encryption
  • Running ETL processes, based on SSIS and SSRS currently
  • Following best practices in data movement such as logs and error handling
  • Maintaining a consistent quality of work and rigorous attention to detail
  • Ability to working collaborative across teams such as Developers, IT and Data Science

Extra's that would awesome:

  • Python skills
  • Exposure, or willingness to learn, machine learning techniques
  • Prior experience of managing repository of machine learning models

Summary You will be joining a well-established, cutting edge DevOps team within a multi-national fintech. This position would work primarily with the company's fast growing Data Science team to scale up the existing ETL pipelines, automate end-to-end data science prototyping and communications and catalogue the model-store of machine learning and deep learning models. You would also be responsible for managing the day-to-day performance of an internal data warehouse.

Reference: 1056295560

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