Analytics Engineer

Exinity; Greater London; On-site; GBP 50,000 - 70,000; Full time

Job summary

A leading UK data technology firm is seeking an Analytics Engineer to design and operate their Insight Environment. The role involves developing scalable data pipelines, maintaining data quality, and supporting machine-learning models. Ideal candidates will have strong skills in Python, SQL, and an understanding of data governance. The position offers exposure to a modern data stack, fostering innovation and career growth. Comprehensive benefits and career-defining opportunities await the right data enthusiast.

Benefits

40 Days of Holiday including Bank Holidays

World-class private health insurance with dental coverage

Significant Flexible Benefits budget

Employee Assistance Program

Life Insurance

Critical Illness Insurance

Qualifications

• Strong experience in data or analytics engineering roles.
• Solid working knowledge of PySpark in data processing.
• Practical understanding of machine learning model lifecycle.

Responsibilities

• Own and evolve core datasets within the Insight Environment.
• Design and maintain production-grade data models and transformations.
• Operationalise machine learning models and data science workflows.

Skills

Python

SQL

PySpark

dbt

BigQuery

Databricks

Prefect

Education

Degree in Computer Science/ Data Science/ Engineering

Tools

Adobe Analytics

Power BI

Tableau

Job description

As an Analytics Engineer you will play a central role in designing building and operating our Insight Environment. You will be responsible for developing reliable scalable data pipelines modelling data for analytical and machine-learning use cases and ensuring high standards of data quality and observability across the platform.

You will work across the analytics data engineering and ML lifecycle. Owning production-grade data transformations orchestrating workflows and supporting the deployment and monitoring of machine-learning models. While you will engage with event-level and marketing data where relevant your primary impact will be in strengthening the engineering foundations that enable trusted analytics and ML at scale. Your work will directly support data-driven decision-making by ensuring our data and models are robust performant and production-ready.

Key Responsibilities

• Data Platform Ownership: Own and evolve core datasets and data domains within the Insight Environment applying strong data governance quality controls and stewardship across the platform.
• Analytics Engineering & Data Modelling: Design and maintain production-grade data models and transformations using dbt and BigQuery providing reliable well-structured data for analytics reporting and downstream ML use cases.
• Machine Learning & ML Ops Enablement: Operationalise machine learning models and data science workflows in Databricks supporting scalable deployment monitoring and lifecycle management of models in production.
• Workflow Orchestration & Reliability: Own the orchestration layer of the Insight Environment (Prefect) ensuring resilient observable and well-documented data workflows across ingestion transformation and activation.
• Data Integration & Activation: Build and manage data pipelines including RETL and activation workflows (e.g. via RudderStack) to ensure timely and consistent data flow between analytical operational and ML systems.

Qualifications

• Strong experience in data or analytics engineering roles with advanced proficiency in Python and SQL for building and maintaining production-grade data pipelines and models.
• Solid working knowledge of PySpark or similar distributed computing frameworks in real-world data processing environments.
• A degree in computer science data science engineering or a related field or equivalent professional experience demonstrating the same depth of technical capability.
• A practical understanding of how machine learning models are productionised including deployment monitoring and lifecycle considerations.
• Proven experience in data preparation and modelling with a strong focus on accuracy reliability and reusability across analytical and ML use cases.
• Experience designing and operating orchestrated data workflows with an appreciation for reliability observability and maintainability.
• Familiarity with Reverse ETL concepts and data activation patterns and the ability to apply them to real business problems.
• Strong problem-solving skills and the ability to communicate clearly and effectively with analytics data science and engineering stakeholders.

Why you'll love this role

In this role youll be at the forefront of data technology working with an advanced modern data stack that includes industry-leading tools such as dbt Databricks BigQuery and Prefect. Youll not only apply these powerful tools to propel our data infrastructure forward but also continuously learn and master them. Our team thrives on innovation and efficiency so youll have the chance to contribute to and shape our evolving data ecosystem. The role is designed to be a career-defining opportunity for a data enthusiast who is eager to explore the depths of analytics engineering and take ownership of projects that push the boundaries of what our data can achieve.

Benefits

• 40 Days of Holiday including Bank Holidays which you can take flexibly when you want.
• World class private health insurance with dental coverage.
• Significant Flexible Benefits budget to spend on the things that matter the most to you.
• Employee Assistance Program
• Life Insurance
• Critical Illness Insurance

Remote Work :

No

Employment Type :

Full-time

Key Skills Adobe Analytics,Data Analytics,SQL,Attribution Modeling,Power BI,R,Regression Analysis,Data Visualization,Tableau,Data Mining,SAS,Analytics

Experience: years

Vacancy: 1