Senior Data Engineer (Python/PySpark & SQL)

Datatech
London, United Kingdom
Last month
Applications closed

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Senior Data Engineer (Python/PySpark & SQL) London (Hybrid - 3 days in office | Monday, Tuesday, Wednesday) Up to £85,000 dependent on experience Ref: J13073 We're working with a fast-growing AI SaaS business where data sits at the core of everything they build. They're looking for a Senior Data Engineer to take ownership of the pipelines that power their platform. You'll be working with real-world, messy data and shaping it into reliable, decision-ready datasets used across product, analytics, and machine learning. Python/PySpark and SQL are central to the role. The Role: ·You'll design and maintain data pipelines, handle edge cases, and ensure data quality as the platform scales. ·The environment is modern and cloud-based, using tools such as AWS, GCP or Azure, alongside Spark, Snowflake or BigQuery. ·You'll also play a key role in supporting and mentoring other engineers through code reviews and collaboration. ·You'll be joining a supportive team that values different perspectives, encourages thoughtful problem solving, and gives engineers the space to contribute in their own way. What we're looking for: ·Strong Python and SQL experience in production ·Experience with Spark, Snowflake, BigQuery or similar ·Cloud experience (AWS, GCP or Azure) ·Comfortable working with complex, messy data ·Experience owning pipelines end-to-end ·Collaborative mindset with mentoring experience If you enjoy building the data foundations behind AI products, this could be a great fit. Get in touch today to find out more Right to work in the UK required (no sponsorship available) If you have a friend or colleague who may be interested, referrals are welcome. For each successful placement, you will be eligible for our general gift or voucher scheme. Datatech is one of the UK's leading recruitment agencies specialising in analytics and is the host of the critically acclaimed Women in Data event. For more information, visit (url removed) <(url removed)

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