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Analytics Engineer at BIP.Verco – Data Science and Management

BIP Group
1 day ago
Full-time
On-site
London, United Kingdom
Data Analyst
Description

Role: Analytics Engineer

Business Unit: BIP.Verco – Data Science and Management
Reporting to: Head of Service, Data Science and Management
Location: TBC

About BIP

At BIP, we are a global consultancy that combines strategic thinking with digital and technological expertise to deliver lasting value for our clients. Within BIP, BIP.Verco is a mission-led environmental consultancy helping organisations address climate change and wider sustainability challenges.

Our teams work with some of the world’s largest organisations to measure, manage and reduce environmental impacts. By combining sustainability expertise with data and technology, we deliver solutions that enable clients to make meaningful progress towards their climate and sustainability goals.

Joining BIP.Verco means becoming part of a collaborative, high-performing team with a strong commitment to professional development and impact-driven work.

Role Overview

We are looking for an Analytics Engineer to join our Data Science and Management team. This role is ideal for someone with experience as a Data Engineer, Analytics Engineer or BI Developer working in a delivery environment.

You will work closely with sustainability consultants and analysts to design and implement scalable data solutions that support environmental accounting and sustainability reporting.

The role focuses on delivering pragmatic, incremental improvements rather than large-scale platform builds. You will own small-to-medium analytics engineering workstreams end-to-end β€” from requirement gathering and solution design through to build, validation, documentation and handover.

Your work will help transition the organisation from isolated, bespoke analytical tools towards integrated and scalable data platforms.

Key Responsibilities

In this role you will:

  • Collaborate with sustainability consultants to understand analytical requirements and business needs, both client-specific and internal.
  • Design, build and maintain reliable ETL pipelines and data models to support sustainability analytics.
  • Develop scalable and robust data and analytical solutions that improve productivity, enable new insights and reduce risk of data errors.
  • Build data models and analytics datasets from scratch and automate pipelines for repeatable data processing.
  • Maintain and iteratively improve existing legacy data solutions while supporting the implementation of new technologies.
  • Contribute to defining and implementing the organisation’s data technology stack and strategy.
  • Develop reusable analytical modules and solutions that can be scaled across projects and integrated into broader software offerings.
  • Ensure solutions are well documented, tested and validated, with appropriate data quality checks.
  • Support knowledge sharing within the team and contribute to the ongoing development of data capabilities across the business.
  • Ensure adherence to data governance, security policies and best practice development standards.

Team Contribution & Ways of Working

While this role does not include formal line management responsibilities, you will be expected to contribute as a senior member of the team, supporting colleagues through knowledge sharing and collaborative problem solving.

As part of our consultancy environment, time allocation typically includes:

  • ~55% developing client-facing data solutions (DBMS / ETL)
  • ~15% developing internal tools and operational improvements
  • ~10% contributing to project delivery
  • ~10% supporting sales and solution scoping
  • ~10% training, development and internal activities

You will work closely with the Head of Service to support the evolution of the company’s data strategy, transitioning from bespoke tools (e.g. Excel or Power BI) to integrated solutions built on modern data platforms and relational databases.

Skills, Experience & Qualifications

Essential Professional Skills

  • Strong communication and stakeholder engagement skills, with the ability to collaborate effectively with both technical and non-technical colleagues.
  • Excellent problem-solving and solution design capabilities, adapting existing tools to meet new requirements within defined constraints.
  • Ability to work from informal or evolving briefs, identifying and delivering the most practical and impactful solution.
  • Strong planning and organisational skills, managing workstreams and tracking delivery against objectives.
  • High level of attention to detail, including the ability to identify errors and design robust validation processes.
  • Ability to self-manage workload and priorities to meet agreed deadlines and project goals.
  • Commitment to working within organisational policies, governance and ways of working.

Essential Technical Skills

  • Degree in Computer Science or a related discipline, or equivalent practical experience.
  • Strong numerical and analytical skills.
  • Experience designing, building and maintaining DBMS, OLAP and ETL frameworks, including data pipelines and analytics datasets.
  • Strong knowledge of relational databases and dimensional modelling (e.g. star schema).
  • Fluency in SQL, with working knowledge of Python or R.
  • Experience with Azure Synapse Analytics and/or Microsoft Fabric, including tools such as:
    • Data Factory
    • Notebooks
    • ASQL
    • OneLake
  • Experience developing data models and visualisations using Excel and Power BI.
  • Understanding of data quality management, testing routines and validation frameworks.
  • Experience implementing version control and deployment processes (e.g. Git and CI/CD).

Desirable Skills

  • Experience with Microsoft Office 365 integrations.
  • Previous experience in a consulting environment, particularly working with sustainability data.
  • Experience designing Power BI semantic models and DAX.
  • Experience using Power BI Service for content sharing and governance.
  • Interest in contributing to the development and evolution of a growing data team, with a willingness to adapt and innovate.