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For Companies At a Glance
- Tasks: Design and maintain scalable data solutions for analytics and reporting.
- Company: Join a scaling FinTech that's revolutionising the industry.
- Benefits: Enjoy hybrid work options and competitive salary of £70-80K.
- Why this job: Be part of a data transformation journey and shape a data-driven future.
- Qualifications: 3+ years in data engineering, proficient in SQL, Python, and AWS tools.
- Other info: Collaborate in Agile teams and promote self-service data models.
The predicted salary is between 60000 - 84000 £ per year.
Our client, a scaling FinTech, is looking for a skilled Data Engineer to design, build, and maintain scalable data solutions that empower analytics, reporting, and self-service across the business.
Key Responsibilities
- Build and maintain robust ELT pipelines and cloud-based data warehouses (e.g., AWS Redshift)
- Model curated data layers to support analytics and decision-making
- Develop and manage reusable, high-quality data products
- Promote self-service with intuitive data models and BI tool integration
- Ensure compliance, data governance, and security best practices
Essential:
- 3+ years’ experience in data engineering and warehousing
- Proficiency with SQL, Python, and AWS tools (Redshift, Glue, S3, Lambda, etc.)
- Strong grasp of data modeling, governance, and pipeline orchestration
- Excellent communication and collaboration skills in Agile teams
Desirable:
- Experience with dbt, Airflow, Monte Carlo, and BI tools (Power BI, Tableau, QuickSight)
- Knowledge of data product principles, real-time pipelines, and data enablement programs
Join to shape a data-driven future and unlock the power of trusted, accessible insights. Apply now to be part of our data transformation journey - michael.hodson@interquestgroup.com
Data Engineer AWS employer: InterQuest Group
Contact Detail:
InterQuest Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer AWS
✨Tip Number 1
Familiarise yourself with the specific AWS tools mentioned in the job description, such as Redshift, Glue, and S3. Having hands-on experience or projects showcasing your skills with these tools can set you apart from other candidates.
✨Tip Number 2
Engage with the data engineering community online, especially on platforms like LinkedIn or GitHub. Sharing your projects or insights related to data modelling and ELT pipelines can help you build a network and demonstrate your expertise.
✨Tip Number 3
Prepare to discuss your experience in Agile teams during interviews. Highlighting your collaboration skills and how you've contributed to team success can resonate well with potential employers looking for strong communicators.
✨Tip Number 4
Consider creating a portfolio that showcases your data products and any relevant projects. This could include examples of data pipelines you've built or analytics solutions you've implemented, which will provide tangible evidence of your capabilities.
We think you need these skills to ace Data Engineer AWS
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data engineering, particularly with AWS tools like Redshift and Glue. Use specific examples to demonstrate your skills in building ELT pipelines and data warehousing.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data engineering and your understanding of the FinTech industry. Mention how your skills align with the company's goals and how you can contribute to their data transformation journey.
Showcase Relevant Projects: If you have worked on relevant projects, include them in your application. Describe your role, the technologies used, and the impact of your work. This will help demonstrate your practical experience and problem-solving abilities.
Highlight Soft Skills: In addition to technical skills, emphasise your communication and collaboration abilities. Since the role involves working in Agile teams, showcasing your teamwork experience can set you apart from other candidates.
How to prepare for a job interview at InterQuest Group
✨Showcase Your Technical Skills
Be prepared to discuss your experience with SQL, Python, and AWS tools in detail. Bring examples of projects where you've built ELT pipelines or worked with data warehouses like AWS Redshift to demonstrate your expertise.
✨Understand Data Governance
Familiarise yourself with data governance principles and be ready to explain how you ensure compliance and security in your data engineering practices. This will show that you take data integrity seriously.
✨Communicate Clearly
Since excellent communication is key in Agile teams, practice explaining complex technical concepts in simple terms. This will help you connect with interviewers who may not have a technical background.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about challenges you've faced in previous roles and how you overcame them, particularly in relation to data modelling and pipeline orchestration.
