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Omaze

Staff Data Engineer

London
Posted 2 months ago
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🌍 Location: Holborn, London ⭐ Office Policy: 3 days in person, 2 days at home each week Who We Are: At Omaze, we give our community in the UK and Germany the chance to win luxury homes and other life-changing prizes — all while raising money for the causes they love. Thanks to our Omaze Community, we’ve raised over £100 million for UK charities in just five years. That’s millions helping organisations like Age UK, the RSPCA, British Heart Foundation and Great Ormond Street Hospital Charity deliver life-saving work. And the best part? We’re only just getting started. Omaze is building a business and culture committed to growth and creating significant social impact on a global scale. 🔑 About The Job As a Staff Data Engineer at Omaze, you will be a key member of Omaze’s lean data function. Reporting into the Director of Data Platforms, you're at your best designing pipelines, modelling foundational datasets, and embedding quality and observability into infrastructure that people genuinely trust. You bring strong judgement to architectural decisions, raise the bar through example, and create leverage for analytics engineers, data scientists, and stakeholders across Omaze. You embrace AI-assisted and agentic coding as part of how modern engineering gets done and apply it with the same judgement and rigour you bring to everything else 🔧 What You’ll Be Doing Build and maintain robust ingestion and processing pipelines from our product systems, third-party tools, and external partners, using modern, well-tested code that holds up as the business changes Build the data quality, observability, and lineage frameworks that make decision-critical datasets trustworthy, and make problems easy to find and fix when they happen Work with engineers across the organisation to ensure that events are properly constructed, with the right parameters and nomenclature, so that the data flowing into our platform is trustworthy by design, not by accident (potentially through data contracts) Ensure that data pipelines to external sources (e.g. paid marketing channels such as Meta) are reliably sharing appropriate, compliant data Lay the foundations to support data science and ML work as it grows, e.g. feature pipelines, training datasets, and the platform capabilities that make those things easy when we want them Make the cost of running our data platform visible and well understood, pushing for efficiency in the places it makes sense, and bringing judgement to when ongoing spend is justified by the value it returns Generally take responsibility for data governance and compliance, ensuring that how we collect, store, and use data is responsible, secure, and meets the regulatory bar Omaze operates at Use AI-assisted and agentic coding tools as a natural part of your workflow; knowing when they add leverage, when to interrogate their output, and how to review AI-generated code with the same rigour you'd apply to anything else. 🤩 About You Extensive data engineering experience, with extensive experience across industry-standard data warehousing software (e.g. Databricks, Snowflake, etc.) and server-side tech (e.g. Typescript, DynamoDB, AWS Lambda, API Gateway and AWS CDK) Hands-on experience with modern orchestration tooling (Aiflow, Dagster, etc.), ingestion tooling such as Fivetran (and experience building out custom scripts when the right off-the-shelf connector doesn’t exist) A track record of building data quality, testing, and observability into platforms, not bolting them on afterwards An understanding of data architecture strategies that can scale with the business for the next 4 years (not just the next 4 weeks!) Experience supporting ML workflows / laying the data foundations for them The ability to bar-raise through code review, mentorship, and the standards you set — not because you're told to, but because you understand why they matter 🙌 What’s In It For You Generous stock options scheme 25 days annual leave PLUS Bank Holidays Private medical and dental insurance 9% employer pension contributions, when you contribute at least 2% A generous personal learning and development budget each year to use on training courses, conferences and professional memberships Personal equipment budget to work from home Enhanced family leave policies Life assurance of 4x your salary DEI Statement We actively seek out diversity of thought and experience to drive innovation. We welcome all backgrounds, identities, and perspectives and work hard to ensure that every Omaze employee can bring their authentic self to work at all times.

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Skills

Data Engineering
Data Warehousing
Typescript
DynamoDB
AWS Lambda
API Gateway
AWS CDK
Airflow
Dagster
Fivetran
Data Modeling
Data Governance
MLOps
AI-Assisted Coding
Data Observability
Data Architecture

Location

London, England, United Kingdom

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