Senior Analytics Engineer
Prolific - Remote, UK
Posted Jun 7, 2026
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
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- Salary
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Market context
- U.S. role benchmark (BLS OEWS)
- $111,944 U.S. median for this role
- Projected growth (BLS Employment Projections)
- +13.7% - Much faster than average
Matched to SOC 15-1252 - Data and ML aggregate by role bucket.
Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.
Role
Schedule
- Shift type
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
Senior Analytics Engineer Remote, UK Senior Analytics Engineer Data Prolific Prolific is not just another player in the AI space-we are the architects of the human data infrastructure that's reshaping the landscape of AI development. In a world where foundational AI technologies are increasingly commoditized, it's the quality and diversity of human-generated data that truly differentiates products and models. The role As an Analytics Engineer in the Data Infrastructure Team at Prolific, you'll be at the forefront of transforming and maintaining Prolific's data infrastructure. Your work will be instrumental in redesigning and scaling our data stack, ensuring data pipelines are robust, efficient, and reliable. By owning and optimizing our analytics codebase, you'll empower our BI-focused teams to deliver valuable insights to the entire organization, while driving data accuracy and accessibility. You'll also bridge the gap between technical and non-technical stakeholders, making sure that complex data solutions are clearly understood and aligned with business goals. What you'll bring to the role Expertise in dbt & SQL: Deep experience with dbt and SQL to design, build, and maintain scalable data models. Cloud Technology Knowledge: Strong familiarity with cloud platforms like AWS, GCP etc Data Accuracy Focus: Passion for ensuring high data quality through tests/assertions and robust documentation. Commercial Acumen: Ability to understand business needs and communicate effectively with non-technical stakeholders. Mentorship Ability: Advocate for best practices in logging and data modeling that supports robust and effective analysis, reporting , and experimentation. Collaboration: Skilled at working cross-functionally and translating complex technical concepts into
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