Lead DevOps Engineer

  • Standort

    London, England

  • Branche:

    Banken & Finanzen

  • Vertragsform:


  • Gehalt:


  • Kontakt:

    Phoebe Cheung

  • E-Mail:


  • Referenznummer:

    PCH - Data Science_1602673737

  • Online:

    etwa 1 Jahr

  • Ablaufdatum:


  • Start:


  • Berater:


My client, a top tier global bank is looking for a Lead DevOps Engineer to join their team based in London. This is a PAYE day rate contract role.

What you will be doing:

  • Contributing in designing and developing robust architecture of the Machine Learning platform that would allow to build, host and monitor ML models created by the team.
  • Engagement with various stakeholders within wider function, lead data requirements for various PoC, execute the platform development plan, deploy the solution and manage the change upon implementation.
  • Participate in projects leading to end-to-end cloud native solutions for predictive analytics
  • Work closely with Data Scientists to provide DevOps support to their development of predictive analytics tools, their prototyping and implementation, including but not limited to Chatbot projects.
  • Create Data Platform for Advanced Analytics teams to enable them in creating of end-to-end automation and AI capabilities
  • Package AI/ML solutions developed by Advanced Analytics using Docker/Kubernetes and host them as microservices on cloud (GCP/AWS)
  • Develop and manage CI/CD pipeline for both GCP and AWS infrastructures
  • Create ETL script for sourcing and connecting data from structured and unstructured database
  • Integrate new data management technologies and software engineering tools into existing structures
  • Collaborate with data scientists, data architects and team members on project goals

What we are looking for:

  • Post Graduate qualifications (quantitative MSc / PhD) in Software Engineering, Statistics, Applied Mathematics, Econometrics, Electronic Engineering or any other relevant quantitative discipline.
  • Strong experience in creating infrastructure platforms for auto-scaling Machine Learning solutions (i.e. NLP (Natural Language Processing), RPA (Robotic Process Automation), ChatBot, etc.), experience in developing end-to-end solutions and deploying them.
  • Knowledge of database architectures, ETL scripting for Hadoop-based technologies, SQL-based technologies and NoSQL technologies. Familiarity with data ingestion tools, data analysis tools such as Spark, MLflow, and workflow automation tools like Airflow and Kubeflow.
  • Experience with Google Cloud Platform and services and experience with equivalent services on AWS or Microsoft Azure.
  • Strong experience in at least two of the following: Python, Java, C/C++, SQL, R relevant data visualisation tools.
  • Very good knowledge of Linux system.
  • Experience of working in relevant Software Engineering or Analytics field. Knowledge and understanding of financial services preferred and market conduct landscape is preferred.

Please send your CV to phoebecheung@taylorroot.com

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