Analytics Engineer

Avance Consulting; London; On-site; GBP 50,000 - 90,000; Full time

Job summary

An innovative firm is seeking an Analytics Engineer to bridge the gap between data engineering and analysis. In this role, you will design complex data models, write SQL, and collaborate with talented teams to deliver robust data products. Your expertise will drive innovation and value creation, ensuring data integrity and accuracy while automating data workflows. This is a unique opportunity to work with cutting-edge technologies and contribute to impactful data solutions in a dynamic environment. If you're passionate about data and eager to make a difference, this role is for you.

Qualifications

• Proficiency in SQL for data transformation and analysis.
• Understanding of data warehousing and cloud technologies.
• Experience with data visualization tools like Power BI.

Responsibilities

• Bridge the gap between engineering teams and stakeholders.
• Create and maintain data models for business insights.
• Automate data processes to improve efficiency.

Skills

SQL

Data Modelling

Data Vault

Data Warehousing

GitHub

AWS

Azure

Python

Data Visualization Tools

Terraform

Job description

As an Analytics Engineer, you'll have the chance to write great SQL, design complex data models, collaborate with a talented team, and deliver robust data products alongside Data Architects, Data Scientists, Product Managers, and Data Engineers. You will bridge the gap between data engineering, data architecture and data analysis. Your focus will be on building robust and scalable data workflows to help business functions use internal data assets in an accessible and repeatable manner. This role offers a unique opportunity to combine expertise in architecture, data engineering, and data insights to drive innovation and value creation within our organisation.

Your responsibilities:

Bridge Between Tech and Stakeholders: Act as intermediaries between engineering teams and stakeholders, ensuring clean, transformed datasets. Understand business requirements and translate them into technical specifications

Data Transformation and Management: Manipulate raw data, making it more organised and easier to analyse. Involves creating and maintaining data pipelines and transforming data into structured formats suitable for analysis.

Data Quality Assurance: Develop data validation processes to ensure data integrity and accuracy.

Collaboration with Data Teams: Work closely with data engineers, and data architects to ensure seamless data integration across various platforms. This involves coordinating with different teams to implement data solutions that meet business needs.

Developing and Maintaining Data Models: Create and maintain data models that represent complex business processes and entities, which are crucial for generating insights and supporting decision-making.

Automation of Data Processes: Automate repetitive data tasks to improve the efficiency and scalability of data operations. May use scripting languages to streamline data workflows.

Create designs for complex projects (data products), iterating existing components or designing new components as needed.

Influence teams within your area of responsibility to design and build components aligned with the overall roadmap and engineering principles.

Collaborate within teams to contribute to the execution of the organisation's technical strategy, focusing on the development and deployment of data solutions.

Lead outcomes, develop stakeholder relationships, and deliver high-quality insights through data storytelling.

Write code following coding standards and best practices, adhering to a test-driven and behaviour-driven development approach.

Assist in architecting systems, designing efficient data solutions, and facilitating technical decision-making.

Insightful domain knowledge to business problems, recommending and implementing data-led approaches.

Ensure high-quality, accurate, and professional outputs that drive real business decisions.

Your Profile

Essential skills/knowledge/experience:

Proficiency in SQL for data transformation, analysis and problem-solving.

Snowflake, DBT, Data Modelling, Data Vault, Data warehousing and GitHub

Understanding of version control systems, continuous integration pipelines, and service-oriented architecture.

Understanding the need for different and appropriate design techniques, such as data vault and data warehousing

Knowledge of Cloud technologies (AWS or Azure) and scripting languages like Python

Working knowledge of modern data architecture frameworks, understanding of Architecture & Engineering

Highly numerate background with the ability to drive business change through data.

Excellent communication skills, capable of explaining complex information in simple terms using available documentation tools.

Strong problem-solving skills and attention to detail, with a curiosity to explore opportunities and solve problems logically.

Delivery of solutions with longevity and maintainability following the latest Agile practices.

Understanding of Relational (and non-relational) databases and when to use them.

Standards/ Principles and knowing when and how to implement frameworks and when to make suggestions for new Standards.

Collaboration & Communication: Strong interpersonal skills with the ability to work cross-functionally with stakeholders, engineers, and analysts.

Knowledge of Data Visualization Tools : Experience with tools such as MicroStrategy / Power BI

Terraform: Experience with Terraform and Terragrunt for infrastructure as code

GenAI: Experience with Generative AI technologies

* Free services are subject to limitations