Duration: 6 months (Posibility to extend)

Location: GSK, King's Cross

Working settings: Remote (once a month)

Pay rate: £614 InsideIR35

At GSK, we want to supercharge our data capability to better understand our patients and accelerate our ability to discover vaccines and medicines. The Onyx Research Data Platform organization represents a major investment by GSK R&D and Digital & Tech, designed to deliver a step-change in our ability to leverage data, knowledge, and prediction to find new medicines.We 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 GSK's 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) .Enabling governance by design of external and internal data: with engineered practical solutions for controlled use and monitoring
Innovative disease-specific and domain-expert specific data products: to enable computational scientists and their research unit collaborators to get faster to key insights leading to faster biopharmaceutical development cycles.Improving engineering efficiency: Extensible, reusable, scalable, updateable

We are looking for an experienced DataOps Engineer to join our growing Data Ops team. As 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:
- 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 across GSK
- Thought leader and partner with wider Onyx 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 life cycle
- Audit as a service

Data Ops Engineers take ownership of delivering high-performing, high-impact biomedical and scientific data ops products and services, from a description of a pattern that customer Data Engineers are trying to use all the way through to final delivery (and ongoing monitoring and operations) of a templated project and all associated automation. They are'standard-bearers for software engineering and quality coding practices within the team and are expected to mentor more junior engineers; they may even coordinate the work of more junior engineers on a large project. They devise useful metrics for ensuring their services are meeting customer demand and having an impact and iterate to deliver and improve on those metrics in an agile fashion

Allegis Global Solutions Limited (AGS)

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