Analytics Engineer / Data Engineer

OpenSource; Remote; GBP 80,000 - 100,000; Full time

Job summary

A fast-growing SaaS company in the UK is seeking an Analytics Engineer / Data Engineer to aid in scaling their data and analytics platform. This role focuses on SQL modeling, data quality, and transforming analytics data for stakeholder use. Candidates should have strong SQL skills, hands-on experience with dbt or similar tools, and proficiency in Python. The position offers a competitive salary with additional perks, including health insurance and a pension plan.

Benefits

Competitive salary

Performance-related bonus

Private health insurance

Generous annual leave allowance

Enhanced pension options

Qualifications

• Strong background in analytics engineering or data engineering.
• Deep experience with SQL and analytical data modeling.
• Comfortable owning production data and supporting it end to end.

Responsibilities

• Design, build, and maintain analytics-ready data models using SQL.
• Own analytics data in production, including monitoring, alerting, and incident resolution.
• Work closely with analysts, engineers, and product teams on cross-functional initiatives.

Skills

Analytics engineering

SQL

Data modelling

Python

dbt or similar frameworks

Cloud data warehouses experience

Data quality improvement

Tools

Snowflake

BigQuery

Redshift

Job description

About the Company

We’re partnering with a fast-growing, product‑led SaaS company to hire an Analytics Engineer / Data Engineer to help scale a modern data and analytics platform.

About the Role

This role sits between data engineering and analytics, with a strong focus on SQL modelling, data quality, and analytics‑ready datasets rather than raw ingestion‑heavy pipelines. You’ll take ownership of production analytics, enable stakeholders to self‑serve with confidence, and play a key role in shaping how data is used across the business. It’s a great fit for someone who enjoys building reliable data foundations, working close to real business use cases, and owning data end to end.

Responsibilities

Analytics & Data Modelling

• Design, build, and maintain analytics‑ready data models using SQL
• Define and maintain trusted metrics and semantic layers
• Translate business and analytical requirements into robust, reusable datasets
• Improve documentation and transparency of data flows and models

Data Pipelines & Production Ownership

• Build and support ELT pipelines that power reporting, analytics, and data products
• Own analytics data in production, including monitoring, alerting, and incident resolution
• Improve data freshness, reliability, and consistency across the platform
• Optimise the data warehouse for performance, cost, and accessibility

Data Quality & Engineering Standards

• Implement testing, validation, and CI / CD practices for analytics code
• Improve observability around data quality, volume anomalies, and model health
• Contribute to governance practices such as lineage, documentation, and access control

Collaboration & Enablement

• Work closely with analysts, engineers, and product teams on cross‑functional initiatives
• Enable stakeholders to self‑serve analytics safely and effectively
• Balance speed, quality, and long‑term maintainability when making technical decisions

Qualifications

• Strong background in analytics engineering or data engineering
• Deep experience with SQL and analytical data modelling
• Hands‑on experience with dbt or similar transformation frameworks
• Proficiency in Python for data manipulation and pipeline support
• Experience working with cloud data warehouses (Snowflake, BigQuery, Redshift, or similar)
• Solid understanding of data warehousing concepts and modern ELT workflows
• Comfortable owning production data and supporting it end to end
• Strong communication skills and experience working cross‑functionally

Required Skills

• Experience consuming data from event streams
• Familiarity with modern table formats (e.g. Iceberg or similar)
• Exposure to BI and dashboarding tools
• Experience improving data observability and monitoring
• Comfort working in Linux or Unix environments

Preferred Skills

• High ownership of a modern analytics platform
• Clear impact on how data is used across the business
• Strong collaboration with product, engineering, and analytics teams
• Opportunity to shape modelling standards, tooling, and best practices
• Remote‑first working with flexibility and autonomy

Pay range and compensation package

• Competitive salary with performance‑related bonus
• Enhanced pension with salary sacrifice options
• Private health insurance and life assurance
• Generous annual leave allowance (including public holidays)
• Long‑term benefits such as extended leave after tenure