At a Glance
- Tasks: Transform raw data into trusted datasets that drive decision-making.
- Company: Join a fast-growing company on a mission to unlock potential through data.
- Benefits: Competitive salary, equity, 25 days off, and private healthcare.
- Why this job: Shape the future of data engineering in a supportive, impactful environment.
- Qualifications: Strong SQL skills, experience with dbt, and familiarity with modern data stacks.
- Other info: Collaborative team culture with mentorship and career development opportunities.
The predicted salary is between 28800 - 48000 £ per year.
We’re a fast-growing company on a big mission: to unlock the potential of every person, team, and organization on the planet. 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 offers an all-in-one solution for frontline workers, allowing 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 optimizing 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! Shape the direction of data engineering at Blink from the ground up. Work in a lean, collaborative team with high autonomy and impact, helping to unlock the value of unique, high-quality datasets.
💰 Benefits include:
- Competitive salary – and equity in the company.
- A quirky, spacious, natural light-filled office in London.
- 25 days a year off (plus public holidays!)
- Learning development focus, plus mentorship options.
- We’ll do everything we can to get you to the top of your game.
- Private healthcare, Ride2Work, pension scheme.
At Blink, we're committed to creating an inclusive and diverse culture where our people feel they truly belong. We value and respect individual differences, so all applications will receive fair and equal consideration without regard to ethnicity, religion, gender, gender identity or expression, sexual orientation, nationality, disability or age.
Analytics Engineer 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 in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, models, and any cool analytics work you've done. This is your chance to demonstrate your expertise and make a lasting impression.
✨Tip Number 3
Prepare for interviews by brushing up on your SQL and dbt knowledge. Be ready to discuss your past experiences and how they relate to the role. Practice common interview questions and think about how you can highlight your adaptability and problem-solving skills.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in being part of our mission at Blink. Don’t miss out on this opportunity!
We think you need these skills to ace Analytics Engineer in London
Some tips for your application 🫡
Show Your Passion for Data: When writing your application, let us know why you're passionate about data and analytics. Share any personal projects or experiences that highlight your enthusiasm for transforming raw data into actionable insights.
Tailor Your Application: Make sure to customise your CV and cover letter to reflect the specific skills and experiences mentioned in the job description. We want to see how your background aligns with our mission and the role of Analytics Engineer.
Highlight Your Technical Skills: Don’t forget to showcase your SQL proficiency and experience with dbt or similar tools. We’re looking for someone who can hit the ground running, so be clear about your technical capabilities and any relevant projects you've worked on.
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 this exciting opportunity at Blink!
How to prepare for a job interview at Blink - The Employee App
✨Know Your SQL Inside Out
As an Analytics Engineer, you'll need to demonstrate strong SQL skills. Brush up on writing and optimising complex queries, and be ready to discuss your experience with joins, window functions, and performance tuning. Practise explaining your thought process when solving SQL-related problems.
✨Familiarise Yourself with dbt
Since you'll be working with dbt or equivalent tools, make sure you understand how to build models, tests, and documentation. Be prepared to share examples of your past work with dbt, including any challenges you faced and how you overcame them.
✨Understand Data Warehousing Concepts
Get comfortable with key data warehousing concepts like star schemas, slowly changing dimensions, and partitioning. During the interview, you might be asked to explain these concepts or how you've applied them in previous roles, so have some real-world examples ready.
✨Show Your Collaborative Spirit
Collaboration is key in this role, so be ready to discuss how you've worked with analysts, BI users, and other stakeholders in the past. Highlight your communication skills and adaptability, especially in a fast-paced environment like a startup, to show that you're a team player who can bridge technical and non-technical gaps.