At a Glance
- Tasks: Transform raw data into trusted datasets that drive decision-making.
- Company: Join Blink, a mission-driven tech company revolutionising employee experience.
- Benefits: Competitive salary, stock options, 25 days leave, and private healthcare.
- Why this job: Be the first dedicated data engineer and shape analytics at Blink!
- Qualifications: Strong SQL skills, experience with dbt, and familiarity with modern data stacks.
- Other info: Dynamic startup environment with opportunities for growth and collaboration.
The predicted salary is between 75000 - 95000 £ per year.
Join a high-growth, mission-driven tech company that is transforming the future of work.
Location: London (Old Street office, 3 days/week)
Reports to: CISO.
Salary: £75-£95k + equity.
About Blink: 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 such as Domino's, JD Sports, and McDonald's.
We are passionate about data being at the core of our decision-making process. After seeing the impact our analytics have had on customers, we know they feel the same. We are now on a mission to make our customer analytics capabilities a successful revenue stream at Blink! Our app allows us to collect data on everything from employee engagement and turnover to survey results, shift booking, and payslips. This potential to transform both our own and our customers' decisions makes analytics at Blink an incredibly exciting opportunity!
The Role: As our first dedicated data engineer, you will be the bridge between data infrastructure and analytics. You will own how raw data is turned into trusted, well-modelled datasets that power decision-making. This means building and optimising dbt models, defining core business metrics, establishing data quality standards, and collaborating closely with our BI team and stakeholders.
Key Responsibilities:
- Build, maintain, and optimise data transformations, models, and pipelines in dbt (or equivalent) – including testing, documentation, and version control.
- Define, own, and monitor business metrics and models (e.g. dimension tables, slowly changing dimensions, aggregates).
- Collaborate with analysts, BI users, data scientists, and business stakeholders to translate data requirements into reliable data products (tables, views, metrics).
- Ensure data quality, consistency, and observability (tests, monitoring, alerting).
- Optimize SQL queries and transformations for performance in your data warehouse/lakehouse environment.
- Support or own CI/CD workflows around analytics (e.g. git, reviews, deployment of transformation code).
- Build or maintain upstream data pipelines or ingestion processes when required.
Requirements:
- Strong proficiency in SQL – writing and optimising complex queries, joins, window functions, performance tuning.
- Experience with dbt (or equivalent) – building models, tests, documentation, version control.
- Understanding of data warehousing concepts (star schemas, snowflake, slowly changing dimensions, partitioning, clustering).
- Experience working in a modern data stack (e.g. BigQuery, Snowflake, Redshift, Databricks, etc.).
- Comfortable working downstream (with BI/analytics users) and upstream (pipelines, ingestion) contexts.
- Familiarity with BI tools (we use ThoughtSpot and Power BI).
- Proficient in Python.
- Solid software engineering skills, including version control, testing, and CI/CD.
- Versatile and adaptable – comfortable working across the stack and able to rapidly learn new tools and solve novel problems.
- You are a great communicator, equally comfortable engaging with technical and non-technical stakeholders.
- Experience in a lean or startup environment is a plus.
Benefits:
- Competitive salary.
- Stock options on start-up 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.
At Blink, we are committed to building an inclusive and diverse culture where everyone feels they truly belong. We value individual differences and welcome applicants from all backgrounds.
Analytics Engineer employer: Blink - Employee Experience Platform
Contact Detail:
Blink - Employee Experience Platform Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer
✨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 application noticed.
✨Tip Number 2
Show off your skills in real-time! If you get the chance, ask for a technical interview or a coding challenge. This is your moment to shine and demonstrate your SQL and dbt prowess.
✨Tip Number 3
Prepare for those behavioural questions! Blink values communication, so think of examples where you've collaborated with both technical and non-technical teams. We want to see how you can bridge that gap!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets into the right hands. Plus, it shows you’re genuinely interested in being part of the Blink team.
We think you need these skills to ace Analytics Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the Analytics Engineer role. Highlight your SQL skills, experience with dbt, and any relevant projects that showcase your data modelling expertise. We want to see how you can bridge the gap between data infrastructure and analytics!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data and how it drives decision-making. Mention specific experiences that align with our mission at Blink and how you can contribute to transforming employee engagement through analytics.
Showcase Your Problem-Solving Skills: In your application, don’t just list your skills—give examples of how you've tackled challenges in previous roles. Whether it’s optimising SQL queries or collaborating with stakeholders, we love to see how you approach problem-solving in a dynamic environment.
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 you’re keen on joining our team at Blink!
How to prepare for a job interview at Blink - Employee Experience Platform
✨Know Your SQL Inside Out
Since strong SQL proficiency is a must for the Analytics Engineer role, make sure you brush up on writing and optimising complex queries. Prepare to discuss specific examples of how you've used SQL in past projects, especially focusing on performance tuning and joins.
✨Familiarise Yourself with dbt
As you'll be building models and managing data transformations in dbt, it’s crucial to understand its functionalities. Consider creating a small project using dbt to showcase your skills during the interview. This hands-on experience will help you speak confidently about your capabilities.
✨Understand Data Warehousing Concepts
Get comfortable with key data warehousing concepts like star schemas and slowly changing dimensions. Be ready to explain how these concepts apply to real-world scenarios, as this will demonstrate your depth of knowledge and ability to contribute to Blink's data infrastructure.
✨Communicate Effectively with Stakeholders
Since the role involves collaborating with both technical and non-technical stakeholders, practice explaining complex data concepts in simple terms. Think of examples where you've successfully communicated with different teams, as this will highlight your versatility and communication skills.