DataOps Engineer

London
9 months ago
Applications closed

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My client is seeking to recruit a DataOps Engineer on an initial 6 month contract based in London. It is hybrid and will require 2/3x days onsite per week.

A Data Ops Engineer is a highly technical individual contributor, building modern, cloud-native, DevOps-first systems for standardizing and templatizing biomedical and scientific data engineering, with demonstrable experience across the following areas:

They are a full-stack shop consisting of product and portfolio leadership, data engineering, infrastructure and DevOps, data / metadata / knowledge platforms, and AI/ML and analysis platforms, all geared toward:

  • Building a next-generation, metadata- and automation-driven data experience for scientists, engineers, and decision-makers, increasing productivity and reducing time spent on "data mechanics"
  • Providing best-in-class AI/ML and data analysis environments to accelerate our predictive capabilities and attract top-tier talent
  • Aggressively engineering our data at scale, as one unified asset, to unlock the value of our unique collection of data and predictions in real-time
    Automation of end-to-end data flows: Faster and reliable ingestion of high throughput data in genetics, genomics and multi-omics, to extract value of investments in new technology (instrument to analysis-ready data in 12h).

  • Deliver declarative components for common data ingestion, transformation and publishing techniques
  • Define and implement data governance aligned to modern standards
  • Establish scalable, automated processes for data engineering teams
  • Thought leader and partner with wider data engineering teams to advise on implementation and best practices
  • Cloud Infrastructure-as-Code
  • Define Service and Flow orchestration
  • Data as a configurable resource (including configuration-driven access to scientific data modelling tools)
  • Observabilty (monitoring, alerting, logging, tracing, ...)
  • Enable quality engineering through KPIs and code coverage and quality checks
  • Standardise GitOps/declarative software development lifecycle
  • Audit as a service

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