Data Analytics Engineer: Real-Time Data Pipelines & Platforms

Test Triangle Limited; England; On-site; GBP 60,000 - 90,000; Full time

Job summary

Test Triangle Limited is seeking a Data Platform Engineer to design and maintain scalable data pipelines and data assets for enterprise analytics in the UK. You will implement ETL processes, build robust data models, and ensure data quality across platforms, collaborating with data scientists and engineers.

The role emphasizes secure data movement, real-time and batch analytics, and thorough documentation of architecture and data models to support business insights.

Qualifications

• Experience designing and implementing scalable data pipelines for analytics.
• Strong understanding of data modeling and data architecture principles.
• Ability to set up data quality checks, monitoring and alerts for data flows.

Responsibilities

• Provide technical input on data platforms and consumption engines to enhance analytics.
• Design, build and maintain data pipelines from source to target ensuring secure data movement.
• Develop and maintain data assets to enable enterprise querying and analytics.
• Manage datasets to support feature engineering, APIs and ingestion processes.
• Build, publish and maintain reusable data assets for real-time and analytical consumption.
• Document data architecture and data models (conceptual/logical/physical).
• Implement data integration using ETL and other tools across databases and platforms, preferably with hands-on GCP experience.
• Collaborate with data wranglers, data scientists and development teams.
• Set up data quality checks, monitoring and alerting for analytics data flows.

Skills

Data pipelines

Data modeling

Data quality monitoring

Data architecture

Cross-team collaboration

APIs

Tools

Google Cloud Platform (GCP)

ETL tools

Job description

Test Triangle Limited is seeking a Data Platform Engineer to design and maintain scalable data pipelines and data assets for enterprise analytics in the UK. You will implement ETL processes, build robust data models, and ensure data quality across platforms, collaborating with data scientists and engineers.

The role emphasizes secure data movement, real-time and batch analytics, and thorough documentation of architecture and data models to support business insights.