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- Tasks: Design and maintain data pipelines using Python and AWS to support fintech initiatives.
- Company: Join a purpose-driven fintech organization focused on making a positive impact in finance.
- Benefits: Enjoy a competitive salary, benefits, and the chance to work on innovative projects.
- Why this job: Be part of a collaborative team driving meaningful change in the financial industry.
- Qualifications: Experience in data engineering, Python, AWS, and strong problem-solving skills required.
- Other info: Work once a month in Bristol and contribute to a growing global portfolio.
The predicted salary is between 48000 - 64000 £ per year.
Senior Data Engineer Salary: Up to £80,000 plus benefits Location: Once a month in Bristol Type : Permanent Are you ready to join a dynamic and purpose-driven fintech-for-good organisation that is committed to making a positive impact in the financial industry? Our client believe in leveraging technology for social good, and are seeking a talented Senior Data Engineer to play a crucial role in advancing their mission. If you are passionate about data engineering and are eager to contribute to meaningful projects, this one is for you! As a Senior Data Engineer, you will be a key member of the growing technology team, responsible for designing, developing, and maintaining robust data pipelines that drive informed decision-making and support fintech-for-good initiatives. This role offers an exciting opportunity to work on cutting-edge projects in a collaborative and innovative environment. Your responsibilities will include: Design, implement, and maintain scalable and efficient data pipelines using Python, AWS, and Lambda. Collaborate with cross-functional teams to understand data requirements and deliver solutions that meet business needs. Optimise and troubleshoot existing data infrastructure to ensure performance and reliability. Work closely with data scientists, analysts, and other stakeholders to support data-driven decision-making. Stay current with industry trends and emerging technologies to continuously enhance data engineering capabilities. Skills, experience and qualifications: Proven experience as a Data Engineer, with a focus on designing and implementing data pipelines. Strong proficiency in Python and experience with AWS services, particularly Lambda, S3, Glue, and Athena. Solid understanding of data modeling, ETL processes, and data warehousing concepts. Experience with version control systems (e.g., Git) and agile development methodologies. Strong problem-solving skills and the ability to work independently or collaboratively within a team. Familiarity with financial data and industry regulations. Experience with serverless architecture and infrastructure as code (IaC). This is an opportunity for a Senior Data Engineer to contribute to a thriving niche market and deliver SaaS to a growing global portfolio. *Unfortunately, due to the high volume of applications, not all applicants will receive feedback*
Senior Data Engineer employer: Formula Recruitment
Contact Detail:
Formula Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer
✨Tip Number 1
Make sure to showcase your experience with Python and AWS in your conversations. Highlight specific projects where you've designed and implemented data pipelines, as this will resonate well with the hiring team.
✨Tip Number 2
Familiarize yourself with the fintech landscape and be prepared to discuss how your skills can contribute to social good initiatives. This alignment with their mission can set you apart from other candidates.
✨Tip Number 3
Network with current or former employees of the organization on platforms like LinkedIn. They can provide valuable insights into the company culture and the specific challenges the team is facing.
✨Tip Number 4
Stay updated on the latest trends in data engineering and serverless architecture. Being able to discuss recent advancements or tools during your interview can demonstrate your commitment to continuous learning.
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience as a Data Engineer, especially focusing on your skills in Python and AWS services. Use specific examples of data pipelines you've designed and implemented.
Craft a Compelling Cover Letter: Write a cover letter that reflects your passion for data engineering and the fintech-for-good mission. Mention how your background aligns with the company's goals and how you can contribute to their projects.
Showcase Relevant Projects: If you have worked on relevant projects, describe them briefly in your application. Highlight your role, the technologies used, and the impact of the project, particularly in relation to data pipelines and infrastructure.
Highlight Continuous Learning: Mention any recent courses, certifications, or self-study related to data engineering, AWS, or emerging technologies. This shows your commitment to staying current in the field and enhancing your skills.
How to prepare for a job interview at Formula Recruitment
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and AWS in detail. Highlight specific projects where you designed and implemented data pipelines, and be ready to explain the challenges you faced and how you overcame them.
✨Understand the Company's Mission
Research the fintech-for-good initiatives of the company. Be ready to articulate how your skills and experiences align with their mission and how you can contribute to meaningful projects that make a positive impact.
✨Demonstrate Problem-Solving Abilities
Prepare examples of how you've optimized and troubleshot data infrastructure in previous roles. Discuss your approach to problem-solving and how you collaborate with team members to find effective solutions.
✨Stay Current with Industry Trends
Familiarize yourself with the latest trends in data engineering and fintech. Be ready to discuss emerging technologies and how they can enhance data engineering capabilities within the organization.
