At a Glance
- Tasks: Design and build scalable data pipelines for financial datasets.
- Company: Established financial services business in Manchester with a focus on data innovation.
- Benefits: Competitive salary, hybrid working, and hands-on involvement in modern data infrastructure.
- Other info: Collaborate closely with Data Analysts and BI Developers in a dynamic environment.
- Why this job: Make a tangible impact on data capabilities and influence technical decisions.
- Qualifications: Strong SQL and Python skills, experience with ETL/ELT pipelines and cloud platforms.
The predicted salary is between 65000 - 85000 £ per year.
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.
- #J-18808-Ljbffr
Data Engineer in Manchester employer: Oscar
Join a dynamic and innovative software and Business Intelligence organisation in Hertford, where you'll thrive in a hybrid work environment that promotes flexibility and collaboration. As a Data Consultant, you'll enjoy a varied role with opportunities for professional growth, including managing projects from inception to deployment and engaging with a European customer base. The company fosters a supportive culture that values continuous learning and offers exposure to exciting industry events, making it an excellent employer for those seeking meaningful and rewarding work.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer in Manchester
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Oscar!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Engineer at Oscar.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Oscar.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer at Oscar, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Engineer in Manchester
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Oscar, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Oscar. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Oscar
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Oscar!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
