At a Glance
- Tasks: Design and maintain robust data pipelines for a next-gen enterprise data platform.
- Company: Leading financial services firm launching a new divisional data team.
- Benefits: Competitive day rate, hybrid work model, and potential for long-term contract.
- Other info: Immediate interviews available; great opportunity for career growth.
- Why this job: Join a dynamic team and make a significant impact in data engineering.
- Qualifications: Expert SQL skills and experience with Snowflake, dbt, and ETL tools.
Location: London (Hybrid)
Duration: 6-Month Contract (High potential for 1+ year extension or perm conversion)
Day rate - £370 - £450 per day Inside IR35
The Role
My Client in financial services is launching a new divisional data team to build a next-generation enterprise data platform. Reporting to the AVP of Data Engineering, you will define engineering best practices, build data-intensive pipelines, and bridge the gap between global business units and technical delivery.
Key Responsibilities
- Build & Scale: Design, test, and maintain robust data pipelines and data warehouse architecture.
- Governance & Quality: Lead code/architecture reviews, enforce IT controls, and optimize system quality.
- Mentorship: Provide technical guidance and assistance to junior development staff.
- Collaboration: Partner with global stakeholders to translate business needs into technical outputs.
Requirements & Tech Stack
Core Technical Skills
- Databases: Expert SQL skills; extensive experience with Snowflake and MS SQL Server.
- ETL & Modeling: Strong experience with dbt and at least one ETL tool (Matillion, Fivetran, SNP Glue, or Informatica).
- CI/CD: Hands-on experience with Azure DevOps (or similar) and shell scripting.
- Engineering Principles: Deep understanding of data modeling, curation, orchestration, and TDD/unit testing.
Soft Skills & Nice-to-Haves
- Agile approach, excellent stakeholder communication, and a results-oriented mindset.
- Pluses: Insurance/Reinsurance industry experience, PowerBI/Tableau, SAP, or NoSQL (DynamoDB/Cosmos).
This is an urgent vacancy where the hiring manager is looking to interview immediately.
If interested then apply with a copy of your CV or send the CV to khushboo.pandey@randstad.co.uk
Randstad Technologies is acting as an Employment Business in relation to this vacancy.
Senior Data Engineer employer: Randstad Technologies Recruitment
As a leading financial services provider, our company offers an exceptional work environment in London, where innovation meets collaboration. We prioritise employee growth through mentorship opportunities and a commitment to best practices in data engineering, ensuring that you can thrive in your career while contributing to cutting-edge projects. With a hybrid work model and a focus on fostering a supportive culture, we empower our team to excel and make a meaningful impact in the industry.
Contact Detail:
Randstad Technologies Recruitment 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 your connections in the data engineering field, especially those who might know about opportunities in financial services. A personal recommendation can make all the difference.
✨Tip Number 2
Prepare for those interviews! Brush up on your SQL skills and be ready to discuss your experience with Snowflake and ETL tools. We want you to showcase your technical prowess and how you can contribute to building that next-gen data platform.
✨Tip Number 3
Don’t forget to highlight your soft skills! Being able to communicate effectively with stakeholders is key. Make sure to share examples of how you've collaborated with teams to translate business needs into technical solutions.
✨Tip Number 4
Apply through our website! It’s the quickest way to get your CV in front of the hiring manager. Plus, we’re here to support you every step of the way in landing that Senior Data Engineer role.
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 with SQL, Snowflake, and ETL tools like dbt. We want to see how your skills match the role, so don’t be shy about showcasing relevant projects!
Showcase Your Soft Skills:Don’t forget to mention your communication skills and results-oriented mindset. We value collaboration and an agile approach, so let us know how you’ve worked with stakeholders in the past.
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and focus on what makes you a great fit for the Senior Data Engineer role.
Apply Through Our Website:We encourage you to apply directly through our website for a smoother process. It’s the best way to ensure your application gets into the right hands quickly!
How to prepare for a job interview at Randstad Technologies Recruitment
✨Know Your Tech Stack Inside Out
Make sure you’re well-versed in SQL, Snowflake, and MS SQL Server. Brush up on your ETL tools like dbt and Matillion, as well as Azure DevOps. Being able to discuss your hands-on experience with these technologies will show that you’re the right fit for the role.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles and how you overcame them. This is especially important for a Senior Data Engineer position where you'll need to design and maintain robust data pipelines. Use the STAR method (Situation, Task, Action, Result) to structure your answers.
✨Emphasise Collaboration and Mentorship
Since this role involves working with global stakeholders and mentoring junior staff, be ready to share examples of how you've successfully collaborated in the past. Highlight any experiences where you’ve provided guidance or support to others, showcasing your leadership skills.
✨Understand the Business Context
Research the financial services industry and understand how data engineering plays a role in it. Be prepared to discuss how you can bridge the gap between technical delivery and business needs, demonstrating that you can translate complex data concepts into actionable insights for stakeholders.
