At a Glance
- Tasks: Design and maintain scalable ETL and data pipelines on GCP for banking projects.
- Company: Join a leading financial services firm in Canary Wharf, London.
- Benefits: Enjoy a competitive salary, hybrid working, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on data quality and compliance.
- Why this job: Make an impact in the banking sector with cutting-edge data engineering solutions.
- Qualifications: Experience in Data Engineering, ETL, GCP, SQL, and programming languages like Python or Java.
The predicted salary is between 60000 - 75000 € per year.
We are looking for a hands-on Data Engineer with strong experience in Data Engineering, ETL development, and the Google Cloud Platform (GCP), preferably within the banking or financial services domain.
The ideal candidate should have practical experience in building and maintaining scalable data pipelines, working with large datasets, and supporting cloud-based data integration and transformation initiatives in enterprise environments. This is a pure engineering role and not suited for Architect or managerial profiles.
Key Responsibilities- Design, develop, and maintain scalable ETL and data pipelines on GCP.
- Work with structured and unstructured datasets from multiple source systems.
- Develop and optimize cloud-based data processing solutions.
- Perform data ingestion, transformation, validation, and cleansing activities.
- Collaborate with business, analytics, and technology teams to support data initiatives.
- Ensure data quality, security, governance, and compliance standards are maintained.
- Troubleshoot and resolve production issues related to data pipelines and integrations.
- Support batch and real-time data processing requirements.
- Strong understanding of Data Engineering concepts and ETL methodologies.
- Hands-on experience with GCP-based data engineering solutions and services.
- Strong SQL and data manipulation skills.
- Experience with Python, Java, or Scala.
- Experience in building and maintaining scalable data pipelines.
- Good understanding of data warehousing and distributed data processing concepts.
- Familiarity with cloud-based data architectures and processing frameworks.
- Experience working in Agile delivery environments.
- Experience within Banking or Financial Services domain.
- Exposure to real-time or streaming data processing.
- Understanding of data governance and regulatory compliance requirements.
- Familiarity with CI/CD and version control tools.
Data Engineer employer: NLB Services
As a Data Engineer at our Canary Wharf location, you will join a dynamic and innovative team within the banking sector, where collaboration and professional growth are at the forefront of our work culture. We offer a hybrid working model that promotes work-life balance, alongside competitive benefits and opportunities for continuous learning and development in cutting-edge technologies. Our commitment to data quality and security ensures that you will be part of meaningful projects that drive impactful change in the financial services industry.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the banking and data engineering space on LinkedIn. Join relevant groups, attend meetups, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ETL projects and data pipelines. Use GitHub to share your code and document your processes. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for those interviews! Brush up on your SQL and GCP knowledge, and be ready to discuss your experience with data pipelines. Practice common interview questions and think of examples that highlight your problem-solving skills in real-time data processing.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you. Tailor your application to highlight your hands-on experience with data engineering and cloud solutions, and let us know why you’re the perfect fit for the role!
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 GCP and ETL development. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about data engineering and how your background fits into the banking domain. Let us know what excites you about working with us at StudySmarter.
Showcase Your Technical Skills:We’re looking for strong SQL and programming skills, so make sure to mention your experience with Python, Java, or Scala. Include specific examples of how you’ve built and maintained scalable data pipelines in your previous roles.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, we love seeing candidates who take that extra step!
How to prepare for a job interview at NLB Services
✨Know Your GCP Inside Out
Make sure you brush up on your Google Cloud Platform knowledge. Be ready to discuss specific GCP services you've used for ETL processes and how they can be applied in the banking domain. Having real examples of projects where you've built scalable data pipelines will definitely impress.
✨Show Off Your SQL Skills
Since strong SQL skills are a must, prepare to demonstrate your data manipulation abilities. You might be asked to solve a problem on the spot, so practice writing queries that involve complex joins, aggregations, and data transformations. The more confident you are with SQL, the better!
✨Talk About Team Collaboration
This role involves working closely with various teams, so be ready to share experiences where you've collaborated effectively. Highlight any Agile methodologies you've used and how you contributed to team success. Companies love candidates who can work well with others and support data initiatives.
✨Prepare for Problem-Solving Questions
Expect questions about troubleshooting and resolving production issues related to data pipelines. Think of specific challenges you've faced in past roles and how you overcame them. Showing your analytical thinking and problem-solving skills will set you apart from other candidates.
