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Data Engineer
Data Engineer (GCP / BigQuery / AI Data Pipelines)
Hybrid: 1 day per week in Central London Package: Up to £60,000 + discretionary annual bonus of up to 5% after 12 months
Build modern, AI-enabled data products with real ownership in a growing technology intelligence environment.
The opportunity to join a growing Data & BI function within a global technology-focused business. Contribute to constructing a modern cloud data estate and an intelligence platform, enabling the development of data pipelines, integrations, and products that transform raw data into actionable insights.
The Role
Key Responsibilities
- Design, build, and maintain end-to-end data pipelines, integrations, and orchestration workflows
- Develop and optimise BigQuery-based data warehouses
- Write Python services and scripts for data ingestion, transformation, validation, and automation
- Integrate data from APIs, internal systems, spreadsheets, and third-party providers
- Support AI/LLM-enabled workflows, including classification, enrichment, extraction, and summarisation
- Enhance data quality, reliability, documentation, performance, and security
- Collaborate closely with analysts, product, sales, and commercial teams
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The Company
- International B2B technology firm investing in data, analytics, and intelligence platforms
- A blend of global institutional backing with the flexibility of a fast-growing data function
- Offers varied technical challenges, visible impact, and opportunities to shape how the data team evolves
- Razorpay is expanding rapidly, providing meaningful career progression within a high-trust and high-ownership culture
The Person
We seek a proactive Data Engineer proficient in solving technical challenges and communicating within a non-technical environment.
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Preferred Experience & Skills
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Strong expertise in data engineering, covering ingestion, transformation, modelling, and pipeline development
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Hands-on experience with Google Cloud Platform (GCP), particularly BigQuery
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Confident proficiency in Python and SQL
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Experience with orchestration, scheduling, and cloud-based data services
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Exposure to Cloud Run, Dataform, dbt, Fivetran, Docker, Git, and CI/CD pipelines
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Interest in AI/LLM-enabled data workflows, especially for unstructured data tasks
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Ability to articulate technical decisions clearly
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Natural inclination for initiative—eager to own challenges without overreliance on formal briefs
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Google Cloud certification is valuable but not mandatory; practical experience, sound judgment, and real-world discussions matter more
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