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- Tasks: Design and implement scalable data pipelines to support business intelligence and analytics.
- Company: Join My Money Matters, a fast-growing company transforming financial confidence.
- Benefits: Enjoy competitive salary, remote work options, and opportunities for professional growth.
- Why this job: Make a real impact on financial guidance through innovative data solutions.
- Qualifications: 5+ years in data engineering with strong SQL and Python skills.
- Other info: Collaborative environment with a focus on AI and modern data practices.
The predicted salary is between 48000 - 72000 ÂŁ per year.
Join to apply for the Senior Data Engineer role at My Money Matters. We are on a mission to make everyone feel confident and in control of their finances so they can achieve their life goals faster. Most people feel out of their depth with money. We solve this through expert financial guidance, smart goal‑planning tools, and exclusive products – helping people save for a first home, boost their pension, or plan for retirement. We are looking for an experienced Data Engineer to join our technology team and support the development of scalable data pipelines and infrastructure within our Databricks environment.
Reporting directly to the Business Intelligence Manager, this role will act as the SME for Data Engineering and work closely with teams across the organisation to ensure efficient, reliable data delivery. The Data Engineer will be responsible for designing and maintaining robust data architectures, optimising data processing workflows, and ensuring high standards of data integrity, accessibility, and governance. This role will play a key part in enabling high‑quality analytics and supporting the business with trusted, well‑structured data. In addition, the Data Engineer will help drive the organisation’s data strategy forward, including preparing the data platform for AI use cases and the adoption of tools such as Genie AI in Databricks.
Key Responsibilities
- Data Architecture and Engineering: Design and implement scalable, efficient data pipelines and infrastructure to support business intelligence and analytics initiatives (Databricks, Power Automate). Lead data engineering to build robust, high‑performance data systems that align with business objectives as well as enabling fit for GenAI and Machine Learning datasets. Collaborate with stakeholders across the organisation to understand data requirements and ensure data solutions meet business needs and serve appropriate data.
- Data Pipeline and Workflow Management: Oversee the development, optimisation, and maintenance of data pipelines, ensuring data is collected, processed, and made available for analysis in a timely and accurate manner. Ensure data quality, integrity, and governance across all data systems by implementing best practices for data validation, security, and privacy (Unity Catalog in Databricks). Develop and maintain ETL processes to integrate data from various sources into centralised data warehouses and data lakes.
- Cross‑functional Collaboration: Partner with analysts and business teams to design data architectures that enable effective reporting, analysis, and decision‑making. Act as the primary point of contact for data engineering, ensuring smooth communication between technical teams and business stakeholders. Translate business needs into technical specifications, ensuring the data infrastructure supports both current and future analytics requirements.
- Performance Monitoring and Optimization: Monitor and optimise the performance of data systems and pipelines, ensuring they meet service level agreements (SLAs) and business expectations. Continuously evaluate and implement new technologies and tools to enhance data processing capabilities and improve overall system performance (Zapier, Genie AI).
- Process Improvement and Innovation: Continuously identify areas for process improvements and implement automation to enhance the efficiency and scalability of data workflows. Ensure data storage and processing solutions are optimised for cost and performance, adapting to evolving business needs.
Qualifications
- Education: Desirable Bachelor’s or Master’s degree in Computer Science, Data Engineering, Software Engineering, or a related field.
- Experience: 5+ years of experience in data engineering, data warehousing, or a similar role. Proven experience in designing, building, and maintaining large‑scale data systems and workflows in cloud environments.
- Technical Skills: Expertise in SQL and Python, or other programming languages used for data processing and pipeline development. Strong knowledge of data warehousing solutions (e.g., Snowflake, Databricks, Redshift, BigQuery) and cloud platforms (e.g., AWS, GCP, Azure). Experience with ETL tools, data integration platforms, and data pipeline orchestration tools (e.g., Apache Airflow, Talend, dbt). Knowledge of reporting and Business Intelligence tools (e.g., Power BI, Tableau, Cognos). Familiarity with data governance principles, data security, and privacy standards.
- Analytical and Problem‑Solving Skills: Excellent problem‑solving skills with the ability to design innovative solutions for complex data challenges. Strong ability to troubleshoot data issues, identify root causes, and implement effective resolutions. Experience in performance tuning and optimising data systems for scalability and efficiency.
- Communication and Interpersonal Skills: Strong communication skills with the ability to present complex technical concepts to both technical and non‑technical audiences. Proven time management skills, able to effectively manage workload independently. Ability to work effectively with cross‑functional teams and handle multiple projects simultaneously in a fast‑paced environment.
Senior Data Engineer employer: My Money Matters
Contact Detail:
My Money Matters Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at local meetups. A friendly chat can lead to opportunities you won’t find on job boards.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, especially those involving Databricks or AI tools. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your past projects and how they align with the role at My Money Matters.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Data Engineer role. Highlight your experience with data pipelines, cloud environments, and any relevant tools like Databricks or SQL. We want to see how your skills align with our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data engineering and how you can contribute to our goals at My Money Matters. Don’t forget to mention any innovative projects you've worked on that relate to AI or automation.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled complex data challenges in the past. We love seeing candidates who can think outside the box and come up with creative solutions, especially in fast-paced environments.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at My Money Matters
✨Know Your Data Tools
Make sure you’re well-versed in the tools mentioned in the job description, like Databricks and SQL. Brush up on your knowledge of ETL processes and data warehousing solutions, as these will likely come up during the interview.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex data challenges. Think about how you identified issues, implemented solutions, and what the outcomes were. This will demonstrate your analytical skills and ability to innovate.
✨Understand the Business Context
Research My Money Matters and understand their mission to help people manage their finances. Be ready to discuss how your role as a Data Engineer can contribute to their goals, especially in terms of supporting analytics and driving data strategy.
✨Communicate Clearly
Practice explaining technical concepts in simple terms. You’ll need to communicate effectively with both technical teams and business stakeholders, so being able to translate complex ideas into understandable language is key.