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Data Platform Engineer

Location:
London
Salary:
£75000 - £85000 per annum + benefits
Job Type:
Permanent
Date Posted:
16 days ago
Expiry Date:
08/03/2024
Job Ref:
BBBH105164_1707299553
Start Date:
07/02/2024
Contact:
Niall Wharton
Contact Email:
niall.wharton@xcede.com
Specialism:
CloudSoftware Engineering & ArchitectureDevOpsCloud Engineering & ArchitectureData EngineeringDataSoftware

DATA PLATFORM ENGINEER

London Office x2/3 days a month

OVERVIEW

Xcede are delighted to partner with one of Europe's most exciting HealthTech firms. The organisation is utilising a blend of modern AI expertise & domain specialisation in an effort to improve the industry from an operational perspective, while also making huge inroads on the journey to preventative rather than reactive medicine.

The automated, intelligence-led features of the company's product are their differentiator, and as a result, their Data unit is realistically their most impactful team.

They're currently growing organically based on demand from their customers, leading to the current search for a Data Platform Engineer.

RESPONSIBILITIES

  • Create Data Pipelines for ingestion and delivery while continuing to maintain them, too.
  • Ensure a consistent and optimised Data Platform at the company (with a key focus on scalability and ongoing performance).
  • Work with and store a variety of structured and highly unstructured sources of data.
  • Look after and administer the company's CI/CD environment, Github repositories and VPC.
  • Advise on all Data Architecture and Data Warehousing measures.

REQUIREMENTS

  • Ideally a BSc/ MSc / PhD degree in Computer Science or STEM subject
  • Strong Google Cloud Platform / GCP experience (BigQuery, GCS, Datastream, Dataflow, etc.)
  • Strong Python coding skills
  • Experience with modern development methods and tooling:

  1. containers (e.g., Docker)
  2. container orchestration (Kubernetes / K8s / Google Kubernetes Engine / GKE)
  3. CI/CD tools
  4. Version control (Git, Github, Gitlab)
  5. Orchestration / DAGs tools (e.g., Argo, Airflow, Kubeflow)
  6. Infrastructure as Code (Terraform, etc.)

  • Knowledge of streaming tools (Pub/sub, Kafka, etc.) hugely beneficial

HOW TO APPLY

Please register your interest by sending your CV to niall.wharton@@xcede.com or click the Apply Link.

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Niall Wharton

Niall Wharton

Specialisms: Data, Data Engineering, AI & Machine Learning, AI Research, NLP, Machine Learning, Computer Vision, Generative AI, AI Engineering
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