Data Engineer

Oscar; Manchester; Híbrido; GBP 65 000 - 85 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Hybrid working

Competitive salary £65k-£85k

Resumo da oferta

Oscar in Manchester is seeking a Data Engineer to join its growing data and technology team. This hybrid role focuses on designing, building and maintaining data pipelines using modern cloud platforms to support financial reporting and decision-making.

You will collaborate with Data Analysts, BI Developers and software engineers, optimise ETL/ELT processes, and ensure data quality, governance and security across critical datasets. This is a hands-on role with real impact on business insights.

Qualificações

• Proven Data Engineer with scalable data pipelines.
• Strong SQL, Python and data transformation skills.
• Experience with cloud data platforms (Azure/AWS).
• Knowledge of data warehousing, modelling and governance.
• Experience with Git, CI/CD and testing practices.
• Excellent communication with technical and non-technical stakeholders.

Responsabilidades

• Design, build and maintain scalable data pipelines for financial data.
• Develop and optimise ETL/ELT processes for accuracy and accessibility.
• Create data models and warehouse solutions for reporting and BI.
• Work with cloud platforms to improve scalability and cost efficiency.
• Implement data quality checks and monitoring for data integrity.
• Collaborate with analysts, engineers and stakeholders on requirements.
• Ensure security, governance and regulatory compliance of data pipelines.
• Adopt CI/CD, version control and automated testing in workflows.

Conhecimentos

SQL

Python

ETL/ELT pipelines

Data modelling

CI/CD

Data security & governance

Ferramentas

Azure

AWS

Snowflake

Databricks

dbt

Airflow

Azure Data Factory

Descrição da oferta de emprego

Location: Manchester (Hybrid – 2-3 days per week in the office)

The Opportunity

I'm currently working with an established financial services business in Manchester that is looking to hire a Data Engineer to join its growing data and technology team.

The organisation operates within the financial services sector, working with complex financial datasets and business-critical information to support its operations, reporting and wider commercial objectives. As the business continues to invest in its technology and data capabilities, it's looking to strengthen its data infrastructure and improve how information is collected, processed, managed and utilised across the organisation.

This is a hands-on Data Engineering opportunity where you'll play an important role in designing, building and maintaining data pipelines, developing scalable data solutions and ensuring the quality, accuracy and reliability of business-critical data.

You'll work closely with Data Analysts, BI Developers, software engineers and wider business stakeholders, helping transform complex datasets into accessible, reliable information that supports financial reporting, operational efficiency and better business decision-making.

The role will involve working with modern cloud technologies, improving existing data processes and contributing to the development of a robust data platform. You'll also have the opportunity to influence engineering standards, improve data architecture and support the organisation's longer-term data strategy.

The ideal candidate will have strong SQL and Python skills, experience building production-grade data pipelines and a good understanding of modern cloud data platforms and data warehousing. Experience within financial services, banking, insurance, investment management or another regulated environment would be particularly valuable.

If you're a Data Engineer looking for an opportunity to work with complex financial datasets, modernise data infrastructure and make a tangible impact within an established financial services organisation, this could be an excellent opportunity.

Key Responsibilities

• Design, build and maintain scalable data pipelines to ingest, transform and process large volumes of financial and operational data.
• Develop and optimise ETL/ELT processes, ensuring data is accurate, consistent and readily accessible.
• Build and maintain data models and warehouse solutions to support financial reporting, business intelligence and wider analytical requirements.
• Work with cloud-based data platforms and infrastructure to improve scalability, performance and cost efficiency.
• Develop data integration solutions, connecting internal financial systems, databases, APIs and third-party data providers.
• Implement data quality checks, validation processes and monitoring to maintain the integrity of critical financial datasets.
• Optimise SQL queries, data transformations and pipeline performance.
• Collaborate with Data Analysts, BI Developers, Software Engineers and stakeholders to understand requirements and deliver effective data solutions.
• Ensure data pipelines and infrastructure meet relevant security, governance and regulatory requirements.
• Contribute to data architecture decisions, engineering standards and best practices.
• Implement automated testing, version control, CI/CD and deployment processes across data workflows.
• Identify opportunities to improve existing data infrastructure, automate manual processes and increase engineering efficiency.
• Support the development of a scalable data platform as the organisation's data requirements evolve.

Essential Skills and Experience

• Proven experience working as a Data Engineer or in a closely related data engineering role.
• Strong SQL skills, including query optimisation, complex transformations and working with large datasets.
• Strong Python development skills for data processing, automation and pipeline development.
• Experience designing, building and maintaining production-grade ETL/ELT pipelines.
• Experience with cloud data platforms, ideally Azure, AWS or Google Cloud.
• Knowledge of data warehousing principles, dimensional modelling and database design.
• Experience integrating data from multiple sources, including APIs, databases and third-party systems.
• Understanding of data quality, validation, monitoring and pipeline reliability.
• Experience using Git and version control, alongside collaborative development practices.
• Familiarity with automated testing, CI/CD and deployment best practices.
• Understanding of data security, governance and access management.
• Strong problem-solving skills and the ability to investigate complex data issues.
• Excellent communication skills and the ability to work effectively with both technical and non-technical stakeholders.

Desirable Skills and Experience

• Experience working within financial services, banking, insurance, investment management, fintech or another regulated industry.
• Familiarity with financial datasets, including transaction data, customer information, investment data or financial reporting.
• Experience working with modern data platforms such as Snowflake, Databricks or Microsoft Fabric.
• Experience with orchestration tools such as Apache Airflow, Dagster or Azure Data Factory.
• Familiarity with transformation frameworks such as dbt.
• Experience with cloud services including Azure Data Lake, AWS S3, Azure Functions or equivalent technologies.
• Knowledge of Spark, distributed processing or other big data technologies.
• Experience working with streaming data, event-driven architectures or near-real-time processing.
• Understanding of regulatory data requirements, auditability, data lineage and data governance.
• Familiarity with financial services regulations and reporting requirements.
• Experience building data infrastructure to support business intelligence, advanced analytics or AI-driven applications.

Package and Benefits

• Salary of £65,000 - £85,000, depending on experience.
• Hybrid working, with 2-3 days per week in the Manchester office.
• Opportunity to join an established financial services organisation investing in its data capabilities.
• Hands-on involvement in developing and improving modern data infrastructure.
• Exposure to complex financial datasets and business-critical data projects.
• Opportunity to influence technical decisions and contribute to the evolution of the data platform.
• Close collaboration with Data, Technology and wider business teams.
• A role offering technical ownership, ongoing development and the chance to make a measurable business impact.