At a Glance
- Tasks: Transform raw data into trusted datasets that drive decision-making.
- Company: Join Blink, a mission-driven tech company revolutionising the future of work.
- Benefits: Competitive salary, stock options, generous leave, and private healthcare.
- Why this job: Be part of a meaningful journey with a supportive team in a high-growth environment.
- Qualifications: Strong SQL skills, experience with dbt, and familiarity with modern data stacks.
- Other info: Dynamic startup culture with opportunities for personal and professional growth.
The predicted salary is between 60000 - 84000 £ per year.
Location: London (Old Street office, 3 days/week).
Join a high-growth, mission-driven tech company that’s transforming the future of work.
Reports to: CISO.
£75-£95k + equity.
About Blink
We’re not just closing the digital divide; we’re 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’re making waves worldwide, partnering with industry leaders like Domino’s, JD Sports and McDonald’s. We’re 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’re 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’ll 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. Initially, it’s likely you’ll own these things end-to-end, but over time we’ll build a team around you. While your focus is the modelling layer, this is a scaleup environment and you'll need to be versatile - comfortable influencing upstream data design and pragmatically solving problems across the data stack.
Key Responsibilities:
- Build, maintain, and optimize 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
About you:
- Strong proficiency in SQL - writing and optimizing 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
Why Blink? You will have the opportunity to be part of something impactful, large-scale, and meaningful. Most importantly, you’ll 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!
- 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).
Analytics Engineer (Hiring Immediately) in London employer: Blink - The Employee App
Contact Detail:
Blink - The Employee App Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer (Hiring Immediately) 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
Prepare for the interview by brushing up on your SQL skills and understanding data warehousing concepts. Be ready to showcase how you've tackled real-world data challenges in the past.
✨Tip Number 3
Show your passion for analytics! During interviews, share examples of how data has driven decisions in your previous roles. This will demonstrate that you’re not just skilled, but also genuinely excited about the impact of data.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining the Blink team!
We think you need these skills to ace Analytics Engineer (Hiring Immediately) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored 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 bring value to Blink!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data and how it drives decision-making. Let us know why you're excited about joining Blink and how your skills align with our mission to transform the future of work.
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 optimise data models. We love seeing practical examples of your skills in action.
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 to be part of our Blink family!
How to prepare for a job interview at Blink - The Employee App
✨Know Your SQL Inside Out
Since strong SQL proficiency is a must for this role, make sure you brush up on writing and optimising complex queries. Prepare to discuss your experience with joins, window functions, and performance tuning. Practising some real-world scenarios can help you articulate your thought process during the interview.
✨Familiarise Yourself with dbt
As you'll be building models and managing data transformations in dbt, it’s crucial to understand its functionalities. Be ready to explain how you've used dbt (or similar tools) in past projects, focusing on version control, testing, and documentation. This will show your hands-on experience and readiness for the role.
✨Understand Data Warehousing Concepts
Get comfortable with key data warehousing concepts like star schemas, snowflake, and slowly changing dimensions. You might be asked to explain these concepts or even solve a problem related to them, so having a solid grasp will definitely give you an edge.
✨Show Your Versatility
This role requires adaptability across the data stack, so be prepared to discuss how you've tackled challenges in both upstream and downstream contexts. Share examples of how you've collaborated with analysts and BI users, and highlight your ability to learn new tools quickly. This will demonstrate that you're not just a one-trick pony!