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Staff, Data Engineer

Pay
Pay not listed
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Build and evolve the governed context layer as a product across data, meaning and knowledge

  • Make certified business meaning machine-readable with clear ownership and lineage

  • Define architecture standards for digital workers that generate, test, deploy and monitor pipelines

  • Set rules for what digital workers do autonomously versus what needs human approval

  • Lead incidents that digital workers cannot resolve, from detection to permanent fix

From the employer’s posting
Implement and evolve the governed context layer as a product
Make certified meaning machine-readable
Define the architecture standards and shared frameworks that digital workers use to generate, test, deploy and monitor pipelines
Set the operating model for agent-generated engineering work: what digital workers do autonomously, what requires human approval
Lead the incidents digital workers cannot resolve, from detection to permanent resolution.

What you’ll bring

All qualifications

Core experience

  • 10+ years in data engineering, including substantial time defining data architecture for production AI or ML systems at significant scale or complexity.
  • Bachelor's degree in Computer Science, Data Engineering or a related field, or equivalent practical experience.
  • Experience in a regulated industry, such as life sciences, where data integrity and auditability are mandatory.
  • Experience building context, metadata or semantic infrastructure that AI systems consume, such as catalogues, business glossaries, knowledge graphs or ontologies, exposed to agents over protocols such as MCP.
  • Experience designing and operating AI agents or LLM-powered systems inside data workflows, including evaluation, guardrails and human-in-the-loop controls.
Qualification wording
10+ years in data engineering, including substantial time defining data architecture for production AI or ML systems at significant scale or complexity.
Bachelor's degree in Computer Science, Data Engineering or a related field, or equivalent practical experience.
Experience in a regulated industry, such as life sciences, where data integrity and auditability are mandatory.
Experience building context, metadata or semantic infrastructure that AI systems consume, such as catalogues, business glossaries, knowledge graphs or ontologies, exposed to agents over protocols such as MCP.
Experience designing and operating AI agents or LLM-powered systems inside data workflows, including evaluation, guardrails and human-in-the-loop controls.
Apply at GSK

Posting record

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Actively hiringFirst seen by us 11 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 27, 202611 days ago
Recorded sightings
17
Last seen by us
Nov 7, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 11

Similar jobs usually come down between day 6 and day 54.

At GSK, jobs usually come down by about day 14.

From 11,488 similar postings that came down, and 63 of GSK’s. Coming down is not always a hire.

GSK is hiring

28 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Engineer hiring is picking up
  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • Databricks
Where the posting names them
Skills Artificial Intelligence (AI), Data Analysis, Data Architecture Development, Database Engineering, Databricks Unified Data Analytics Platform, Data Engineering, Data Transformation, ETL Development, Machine Learning (ML), Python (Programming Language), Structured Query Language (SQL) Why GSK?

Your next step

Complete your application on gsk.wd5.myworkdayjobs.com. The employer’s form will show what is required.

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  • Your application status lives in that employer’s Candidate Home, under the same sign-in.

Already applied? Track this application

Has GSK posted this job before?

Yes. We’ve followed one other Staff, Data Engineer job there since October 2026. It is still up.

  1. PhiladelphiaStill up after 12 days, first seen Oct 26
  2. This jobUp 11 days so far, first seen Oct 27

About GSK

People
About 10 in 2023.Benefit plan filings (Form 5500)
Company
Listed as GSK.L.
Layoff notices
Notices this year and last cover 8 people. The latest was filed September 29, 2025.State WARN notices

Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 839, the most 1,314, and the latest week had 1,079.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

Job Purpose :


  • Enterprise AI (EAI) builds the data foundations that GSK's AI systems depend on. In our operating model, digital workers do the hands-on data engineering. They generate pipelines, test and deploy them, monitor them in production and remediate failures. Our engineers design the system those digital workers operate in. 
  • At the centre of that system is a governed context layer. It makes data, meaning, permissions and history retrievable at the moment they are needed, and sits above our data platforms and beneath every experience and agent built on them. 
  • The Staff Data Engineer is accountable for implementing and evolving the governed context layer that humans and digital workers use across EAI, and is EAI's internal authority on data architecture for AI. 

Responsibilities:


  • Implement and evolve the governed context layer as a product: one layer across enterprise knowledge, structured data, business vocabulary and modelled ontologies, queried by humans and digital workers at run time. 
  • Build the capabilities the layer depends on: reliable cataloguing across structured and unstructured data, AI-assisted metadata enrichment, context design for each use case, secure agent access over standard protocols such as MCP, and routing across sources. 
  • Make certified meaning machine-readable so that every number a digital worker returns resolves to one governed definition, with clear ownership and lineage. 
  • Define the architecture standards and shared frameworks that digital workers use to generate, test, deploy and monitor pipelines, reducing the integration cost of each new AI initiative. 
  • Set the operating model for agent-generated engineering work: what digital workers do autonomously, what requires human approval, how quality is evaluated and how incidents escalate. Lead the incidents digital workers cannot resolve, from detection to permanent resolution. 

Required skills:


  • 10+ years in data engineering, including substantial time defining data architecture for production AI or ML systems at significant scale or complexity. 
  • Deep, hands-on experience building AI-grade data infrastructure: feature stores, vector databases, retrieval architectures, streaming data flows and evaluation datasets. 
  • Experience building context, metadata or semantic infrastructure that AI systems consume, such as catalogues, business glossaries, knowledge graphs or ontologies, exposed to agents over protocols such as MCP. 
  • Experience designing and operating AI agents or LLM-powered systems inside data workflows, including evaluation, guardrails and human-in-the-loop controls. 
  • A track record of defining data quality, lineage and governance standards for AI pipelines, including privacy, consent, PII handling and auditability, adopted across multiple data domains. 
  • Expert command of cloud data platforms and infrastructure as code, and a record of setting engineering standards that others adopted

Education:


  • Bachelor's degree in Computer Science, Data Engineering or a related field, or equivalent practical experience. 


Preferred skills:


  • Prior Staff, Principal or equivalent experience in an organisation operating a non-trivial data platform for AI. 
  • Experience in a regulated industry, such as life sciences, where data integrity and auditability are mandatory. 
  • Public technical contributions, such as talks, writing or open source, on data architecture for AI, context engineering or agent-operated data engineering. 

#AGTech


Skills

Artificial Intelligence (AI), Data Analysis, Data Architecture Development, Database Engineering, Databricks Unified Data Analytics Platform, Data Engineering, Data Transformation, ETL Development, Machine Learning (ML), Python (Programming Language), Structured Query Language (SQL)

 

 

Why GSK?

Uniting science, technology and talent to get ahead of disease together.

GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale.

People and patients around the world count on the medicines and vaccines we make, so we’re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.

Inclusion at GSK:

As an employer committed to Inclusion, we encourage you to reach out if you need any adjustments during the recruitment process.

Please contact our Recruitment Team at IN.recruitment-adjustments@gsk.com to discuss your needs.

Important notice to Employment businesses/ Agencies

GSK does not accept referrals from employment businesses and/or employment agencies in respect of the vacancies posted on this site. All employment businesses/agencies are required to contact GSK's commercial and general procurement/human resources department to obtain prior written authorization before referring any candidates to GSK. The obtaining of prior written authorization is a condition precedent to any agreement (verbal or written) between the employment business/ agency and GSK. In the absence of such written authorization being obtained any actions undertaken by the employment business/agency shall be deemed to have been performed without the consent or contractual agreement of GSK. GSK shall therefore not be liable for any fees arising from such actions or any fees arising from any referrals by employment businesses/agencies in respect of the vacancies posted on this site.

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GlaxoSmithKline does not charge any fee whatsoever for recruitment process. Please do not make payments to any individuals / entities in connection with recruitment with any GlaxoSmithKline (or GSK) group company at any worldwide location. Even if they claim that the money is refundable.

If you come across unsolicited email from email addresses not ending in gsk.com or job advertisements which state that you should contact an email address that does not end in “gsk.com”, you should disregard the same and inform us by emailing askus@gsk.com, so that we can confirm to you if the job is genuine.

 

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Bengaluru Luxor North Tower

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