At a Glance
- Tasks: Build and evolve our data platform, ensuring reliable data ingestion and analytics.
- Company: Join Blink, a mobile-first employee experience platform making waves globally.
- Benefits: Competitive salary, stock options, generous leave, private healthcare, and social events.
- Other info: Dynamic environment with opportunities for significant influence and career growth.
- Why this job: Be part of a meaningful journey with an ambitious team in a fast-growing startup.
- Qualifications: Strong SQL skills, experience with data pipelines, and proficiency in Python.
The predicted salary is between 60000 - 80000 € per year.
London (in office 3 days/week)
Reporting to our CISO
We are not just closing the digital divide; we are reconnecting distributed organisations, enabling seamless communication, and re-engaging employees like never before. Blink, a mobile-first employee experience platform, puts everything employees need right in their hands. With teams in Boston, London, and Sydney, we are making waves worldwide, partnering with industry leaders like Domino's, JD Sports and McDonald's. Data plays a critical role in how we build, operate and scale the platform — from powering internal insights to enabling Blink IQ, our customer-facing analytics product. We are looking for a Senior Data Engineer to help shape and scale Blink’s data platform as we continue to grow.
The Role
You will be one of the first dedicated hires in our data function, helping establish the foundations of Blink’s data platform and engineering practices. Your focus will be on the infrastructure and platform layer — building and maintaining data ingestion pipelines, improving reliability and enabling scalable analytics across the business and our customer-facing products. This is a hands-on role with significant influence over how the platform evolves. You will help modernise parts of our stack, improve performance and reliability, and support the development of Blink IQ 2.0, our customer-facing analytics product. You will work closely with engineering, DevOps and stakeholders across the business, and help shape how the wider data function grows over time.
What You’ll Do
- Build and evolve the data platform
- Own and improve data ingestion pipelines across our stack
- Design and implement orchestration for data workflows
- Productionise data processes and ensure they run reliably at scale
- Improve platform reliability and engineering standards
- Establish CI/CD practices across the data platform
- Build monitoring, alerting and data quality checks
- Improve observability across pipelines and workflows
- Support analytics and product insights
- Contribute to the development of Blink IQ 2.0, our customer-facing analytics product
- Help ensure data is reliable, scalable and accessible across the organisation
- Support analytics and reporting needs across teams
- Collaborate across engineering and the business
- Work with DevOps on shared infrastructure and deployment practices
- Support ad-hoc data needs and help stakeholders access reliable insights
- Contribute to architectural decisions as the data platform evolves
What We’re Looking For
- Strong SQL skills, including performance optimisation and complex queries
- Experience building and maintaining data pipelines at scale
- Experience with a modern data stack (e.g. Snowflake, dbt, Fivetran, Debezium or similar)
- Experience with orchestration tools such as Airflow, Dagster or Prefect
- Proficiency in Python for building production data workflows
- Familiarity with data warehousing concepts and modelling patterns
- Experience working with cloud platforms and infrastructure tooling
- Comfortable working across the stack — from ingestion through to analytics use cases
- Strong communication skills and ability to collaborate with technical and non-technical teams
- Startup or scale-up experience is a plus.
Why Blink?
You will have the opportunity to be part of something impactful, large-scale, and meaningful. Most importantly, you will work for a company with a strong purpose, with an ambitious and supportive team embarking on a journey most start-ups can only dream of!
Benefits include:
- Competitive salary.
- Stock options on starting and additional high performer grants annually!
- 25 days’ leave + public holidays.
- Additional time off between Christmas and New Year.
- Private healthcare with AXA.
- 3% employer pension contribution when you contribute 5%.
- Cycle to Work scheme.
- Social events (lunches, breakfasts, nights out).
- Enhanced parental leave.
Senior Data Engineer in London employer: Blink - The Employee App
At Blink, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Senior Data Engineer in our London office, you'll be part of a passionate team dedicated to bridging the digital divide, with ample opportunities for professional growth and development. Enjoy competitive benefits, including stock options, generous leave policies, and a supportive environment that values your contributions and well-being.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer in London
✨Tip Number 1
Network like a pro! Reach out to current employees at Blink on LinkedIn or through mutual connections. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! Prepare a mini-project or case study that highlights your experience with data pipelines and analytics. Bring it up during interviews to demonstrate your hands-on expertise.
✨Tip Number 3
Be ready to discuss your past experiences in detail. Think about specific challenges you've faced in data engineering and how you overcame them. This will show you're not just knowledgeable, but also practical.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in being part of the Blink team.
We think you need these skills to ace Senior Data Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Senior Data Engineer role. Highlight your SQL prowess, data pipeline experience, and any relevant tools you've worked with. We want to see how you can contribute to our data platform!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for data engineering and how it aligns with our mission at Blink. Let us know why you're excited about the opportunity and how you can help shape our data function.
Showcase Your Projects:If you've worked on any cool data projects, don’t hold back! Include links or descriptions of your work that demonstrate your ability to build and maintain data pipelines. We love seeing real-world applications of your skills!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team!
How to prepare for a job interview at Blink - The Employee App
✨Know Your Data Stack
Make sure you’re well-versed in the modern data stack mentioned in the job description, like Snowflake and dbt. Brush up on your SQL skills and be ready to discuss how you've optimised performance in past projects.
✨Showcase Your Pipeline Experience
Prepare examples of data pipelines you've built or maintained at scale. Be specific about the challenges you faced and how you overcame them, especially regarding reliability and scalability.
✨Collaboration is Key
Since this role involves working closely with engineering and DevOps, think of instances where you successfully collaborated with cross-functional teams. Highlight your communication skills and how you’ve supported non-technical stakeholders in accessing data insights.
✨Be Ready for Technical Questions
Expect technical questions around orchestration tools like Airflow or Dagster. Brush up on your Python skills and be prepared to discuss how you would approach building production data workflows.
