Staff Analytics Engineer

Jobtailor; Greater London; On-site; GBP 70,000 - 110,000; Full time

Job summary

Jobtailor in the United Kingdom seeks an experienced analytics or data engineering professional to own data models in a data warehouse and drive ML-ready analytics.

You will pioneer new tools, integrate data sources for ML pipelines, and collaborate with business and engineering teams to build scalable architecture.

This role emphasizes ELT pipelines, real-time features, and strong data transformation expertise.

Qualifications

• 5+ years of experience in analytics or data engineering.
• Strong technical background with a love for complex projects.
• Deep expertise in data modelling and transformation.
• Hands-on experience using tools like dbt.
• Cloud data warehouse experience using platforms like Snowflake or Databricks.
• Track record of building ML features for real-time applications.
• Strong tool-evaluation skills for AI and ML readiness.
• Broad programming knowledge.
• Exposure to real-time streaming frameworks like Apache Flink (insurance domain knowledge is a plus).

Responsibilities

• Create and own key data models in data warehouse
• Pioneer new tools and technologies for advanced analytical features
• Integrate fresh data sources for machine learning pipelines
• Collaborate with business and engineering teams for scalable architecture
• Manage ELT pipelines for reporting systems
• Guide product and engineering teams for analytics and ML requirements

Skills

Data modelling

Transformation

ELT pipelines

Cross-functional collaboration

Analytics

ML features

Tools

dbt

Snowflake

Databricks

Apache Flink

Job description

Responsibilities

• Create and own key data models in data warehouse
• Pioneer new tools and technologies for advanced analytical features
• Integrate fresh data sources for machine learning pipelines
• Collaborate with business and engineering teams for scalable architecture
• Manage ELT pipelines for reporting systems
• Guide product and engineering teams for analytics and ML requirements

Qualifications

• 5+ years of experience in analytics or data engineering
• Strong technical background with a love for complex projects
• Deep expertise in data modelling and transformation
• Hands‑on experience using tools like dbt
• Cloud data warehouse experience using platforms like Snowflake or Databricks
• Track record of building ML features for real‑time applications
• Strong tool‑evaluation skills for AI and ML readiness
• Broad programming knowledge
• Exposure to real‑time streaming frameworks like Apache Flink (insurance domain knowledge is a plus)

Core Competencies

Demonstrates expertise in data modeling, transformation, and integration for machine learning pipelines, with a strong focus on building scalable architectures and advanced analytical features. Proficient in managing ELT pipelines and collaborating with cross‑functional teams to drive analytics and machine learning initiatives.