Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Develop and implement scalable data pipelines and manage data storage solutions.
- Company: Join a global leader in financial services focused on innovative, data-driven solutions.
- Benefits: Enjoy a collaborative environment with opportunities for growth and cutting-edge technology.
- Why this job: Be part of a team that drives business growth through actionable insights and modern data stacks.
- Qualifications: Experience in Python, SQL, and modern data architecture is essential.
- Other info: Work with cross-functional teams to deliver high-quality data solutions.
The predicted salary is between 43200 - 72000 £ per year.
About the company:
The Company is a global leader in providing financial services, specializing in data-driven solutions. With a focus on innovative technologies, the Company aims to help organizations unlock the full potential of their data. Their team is committed to building cutting-edge solutions and driving business growth through actionable insights.
They are looking for a Data Engineer to join their team. The position would be ideal for someone passionate about working with modern data stacks and collaborating with cross-functional teams to deliver high-quality data solutions.
Roles & Responsibilities:
- Your primary role involves developing and implementing scalable data pipelines, ensuring data is efficiently ingested, transformed, and processed from various sources.
- You are required to manage data storage solutions by optimizing data warehouses and cloud storage systems for better performance and accessibility.
- You'll be responsible to maintain data quality and enforce governance policies, ensuring data integrity and following best practices in security.
- Administering the performance of data pipelines and optimizing query performance is an essential part of your role, ensuring smooth data flow and infrastructure scalability.
- Your role also involves collaborating with data scientists, analysts, and engineers to meet data needs, enabling data-driven insights that drive decision-making.
Expectations & Requirements:
- Should have extensive experience in Python and SQL, with a proven track record of creating and managing data pipelines.
- Quite an acquaintance of modern data architecture, including working with Databricks, DBT, and cloud platforms like AWS (S3, EC2, DMS, Kinesis, Lambda).
- Must be skilled in managing semi-structured data formats such as JSON, and have a solid understanding of tools like Apache Spark, Hadoop, and Kafka.
- Ensure that you deliver scalable and efficient data pipelines, while improving the overall infrastructure and query performance.
- Ensuring quality projects are delivered within defined timelines, while collaborating with team members to resolve any technical challenges is essential to this role.
- You are also expected to bring a strong understanding of CI/CD principles and modular coding, contributing to continuous improvements in software delivery.
Data Engineer employer: FinTop Consulting
Contact Detail:
FinTop Consulting Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Familiarize yourself with the specific tools and technologies mentioned in the job description, such as Databricks, DBT, and AWS. Having hands-on experience or projects showcasing your skills with these platforms can set you apart from other candidates.
✨Tip Number 2
Network with current employees or professionals in the financial services sector who work with data engineering. Engaging in conversations about their experiences can provide valuable insights and potentially lead to referrals.
✨Tip Number 3
Prepare to discuss your previous projects involving data pipelines and how you optimized performance. Be ready to share specific examples of challenges you faced and how you overcame them, as this demonstrates your problem-solving skills.
✨Tip Number 4
Showcase your understanding of CI/CD principles and modular coding during interviews. Being able to articulate how these practices improve software delivery will highlight your commitment to quality and efficiency in data engineering.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, SQL, and modern data architecture. Include specific projects where you've developed scalable data pipelines and mention any relevant tools like Databricks or AWS.
Craft a Strong Cover Letter: In your cover letter, express your passion for data engineering and how your skills align with the company's focus on innovative data-driven solutions. Mention your experience with cross-functional teams and your commitment to data quality and governance.
Showcase Relevant Projects: If you have worked on projects involving Apache Spark, Hadoop, or Kafka, be sure to include these in your application. Describe your role and the impact of your contributions on the project's success.
Highlight CI/CD Experience: Since the role requires knowledge of CI/CD principles, make sure to mention any experience you have with continuous integration and delivery processes. This will demonstrate your ability to contribute to software delivery improvements.
How to prepare for a job interview at FinTop Consulting
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and SQL in detail. Highlight specific projects where you developed data pipelines and managed data storage solutions, especially using tools like Databricks and AWS.
✨Demonstrate Your Problem-Solving Abilities
Expect questions that assess your ability to troubleshoot and optimize data pipelines. Share examples of challenges you've faced in previous roles and how you resolved them, particularly in terms of performance and data quality.
✨Emphasize Collaboration
Since the role involves working with cross-functional teams, be ready to discuss your experience collaborating with data scientists, analysts, and engineers. Provide examples of how you contributed to team projects and facilitated data-driven decision-making.
✨Understand CI/CD Principles
Make sure you can explain CI/CD principles and how they apply to data engineering. Discuss any experience you have with modular coding and continuous improvements in software delivery, as this will demonstrate your commitment to best practices.
