Data Engineer

83zero; Greater London; Hybrid; GBP 55,000 - 90,000; Full time

Job summary

83zero is expanding its delivery team and seeks a Data Engineer to help build modern data platforms for clients in financial services and beyond. You’ll work on data pipelines, modeling and analytics projects, collaborating with client stakeholders to deliver scalable solutions using Azure technologies.

The role is client-facing, with office presence in London and two days per week in the office; you’ll contribute to reporting, analytics and operational data use, while maintaining high standards

Qualifications

• Strong commercial experience with Azure data environments.
• Hands-on with Azure Data Factory, Azure Databricks and Azure SQL Server.
• Strong SQL and Python skills.
• Experience in Financial Services (Banks/InsurTech/FinTech).
• Understanding of modern data architectures, including medallion architecture.
• Knowledge of cloud security, IAM and networking concepts.

Responsibilities

• Develop and maintain scalable data pipelines using Azure Data Factory.
• Build and manage ETL processes using SQL and Python.
• Work with Azure Databricks and Azure SQL/SQL Server to process large datasets.
• Design and implement data models using Kimball, 3NF and dimensional modelling.
• Develop metadata-driven pipelines to improve automation and efficiency.
• Work closely with technical teams and clients to understand data requirements.

Skills

Azure data environments

SQL

Python

Azure Data Factory

Azure Databricks

Azure DevOps

Financial Services experience

Tools

Azure Databricks

Azure SQL Server

Azure DevOps

CI/CD pipelines

Job description

I’m currently working with a growing data and technology consultancy who are looking to bring a Data Engineer into their expanding delivery team. The business works with a range of organisations across telecommunications, financial services, insurance and healthcare, helping clients develop modern data platforms and turn complex data into valuable business insights.

Joining a client-facing consulting team, you’ll have the opportunity to work across a variety of data engineering projects, with a strong focus on financial services. You’ll be responsible for building, transforming and structuring large datasets, developing reliable data pipelines and supporting the delivery of data solutions for reporting, analytics and operational use.

You’ll work closely with both technical teams and client stakeholders to understand requirements, design scalable solutions and deliver robust data platforms using modern Azure technologies. The company have offices in London and are looking for someone who is happy to work from the office 2 days per week.

Key Responsibilities

• Develop and maintain scalable data pipelines using Azure Data Factory.
• Build and manage ETL processes using SQL and Python.
• Work with Azure Databricks and Azure SQL / SQL Server to process and manage large datasets.
• Design and implement data models using Kimball, 3NF and dimensional modelling approaches.
• Develop metadata-driven pipelines to improve automation and efficiency.
• Work closely with technical teams and clients to understand data requirements and deliver effective solutions.
• Maintain high standards of data quality, integrity and security throughout the data lifecycle.

Experience Required

• Strong commercial experience working within Azure data environments.
• Hands-on experience with Azure Data Factory, Azure Databricks and Azure SQL / SQL Server.
• Strong SQL and Python skills.
• Previous experience working within Financial Services environments (Banks/Insurance/FinTech)
• Good understanding of modern data architectures, including medallion architecture.
• Understanding of cloud security, IAM and networking principles.
• Comfortable working within Agile delivery environments.
• Experience with CI/CD pipelines, ideally using Azure DevOps or similar.

Nice to Have

• Experience with Apache Airflow or dbt.
• Exposure to BigQuery / GCP.
• Azure or other cloud platform certifications
• Knowledge of data governance and data management frameworks
• Ideal experience working with financial data, regulatory reporting or risk-related datasets