Cognizant
Data Engineer(GCP)

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Data Engineer Opportunity at Cognizant’s Intelligent Process Automation Practice
Excellent opportunity for Data Engineer to be part Cognizant’s Intelligent Process Automation practice. It combines advisory services with deep vendor partnerships and integrated solutions to create and execute strategic roadmaps.
Key Responsibilities
- Developing ETL solutions in GCP including Python and SQL as well as SQL Server including SSIS & T-SQL
- DW development practices (code & configuration management, build processes)
- Enterprise level data warehouse architectures, data modelling concepts, and ETL/ELT best practices
- Take business requirements and work with other team members to estimate and design end-to-end solutions
- Working in Agile delivery models with CI/CD pipelines for automated deployments across data platforms.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Technical Skills
- Development background with exposure to Data Warehousing at scale on both cloud and on-premise
- Experience developing ETL solutions in GCP including Python and SQL as well as SQL Server including SSIS & T-SQL
- Exposure to DW development practices (code & configuration management, build processes)
- Strong understanding of enterprise level data warehouse architectures, data modelling concepts, and ETL/ELT best practices
- Ability to take business requirements and work with other team members to estimate and design end-to-end solutions
- Experience working in Agile delivery models with CI/CD pipelines for automated deployments across data platforms.


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Nice to Haves
- Insurance industry experience
- Exposure to BI reporting toolsets – ideally Power BI
- Demonstrable experience in mentoring or supporting the development of junior team members
- Capability to architect highly scalable distributed systems, using different tools
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