2 months ago
Remote, United KingdomMid Level
Responsibilities
- Build and maintain data pipelines from internal databases, SaaS sources, and streaming systems to analytics, ML, product, and AI consumers.
- Design and implement scalable data infrastructure and data services or APIs that bridge analytical and operational systems.
- Evolve the data platform using Terraform and Kubernetes-based Argo deployments alongside cloud platform engineers.
- Own data quality and observability through monitoring, testing, alerting, and reliability improvements.
- Partner with AI engineers, data scientists, analysts, and product teams to design data solutions.
- Uphold data privacy, security, compliance, documentation, and systems architecture practices.
Requirements
- At least 3 years of experience building and shipping production-grade data systems.
- Strong SQL skills and proficiency in Python or another object-oriented language such as Java or Scala.
- Experience with data pipeline tools including Airflow and dbt.
- Familiarity with Terraform, Kubernetes, or similar infrastructure-as-code and container orchestration tools.
- Experience designing data APIs or services, or strong interest in analytical and operational data systems.
- Ability to optimize data pipelines for performance and reliability and independently ship medium-sized features.
- Understanding of data quality, privacy, security, compliance, testing, code reviews, observability, and documentation.
- Strong analytical, collaboration, problem-solving, and cross-functional communication skills.
Benefits
- Competitive salary and benefits are provided, with no specific compensation amount stated.
- Remote working is available.
- The role offers access to Prolific's human data platform and opportunities related to AI research and innovation.
Tech Stack
Categories
Data Engineering
About Prolific
Prolific builds an online marketplace to recruit verified participants and collect human data for academic research, product studies, and AI model development. Researchers and companies design studies and tasks, pay participants, and Prolific charges platform and service fees; the company also supports data labeling and AI training workflows through managed and self-serve tools. Founded in 2014 and headquartered in London, it is privately held and used by tens of thousands of organizations worldwide.