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For Companies At a Glance
- Tasks: Design and build data pipelines for real-time analytics in a fast-growing digital platform.
- Company: Join a rapidly scaling UK-based consumer platform focused on data-driven growth.
- Benefits: Competitive salary, remote work, and clear progression opportunities.
- Other info: Work remotely with a dynamic team tackling complex data challenges.
- Why this job: Make a real impact on a modern data platform and engineering culture.
- Qualifications: Strong experience in cloud-based data engineering with Python, SQL, and AWS.
The predicted salary is between 90000 - 100000 £ per year.
This is an opportunity to join a fast scaling, digital first consumer platform at a pivotal point in its data journey. They are investing heavily in their data infrastructure and are building a high performing, software led data engineering team to support real time, high volume analytics across the business. You will have genuine influence over how data engineering is done, working on modern tooling and best practice from day one.
The Company
They are a UK based, consumer facing digital platform operating in a highly regulated online environment. Since launching less than a decade ago, the business has grown rapidly, supported by significant recent funding and a strong focus on product, user experience and responsible engagement. Data is central to their growth strategy, and they are building a modern, scalable analytics platform to support this ambition. The team operates fully remotely across the UK and Europe.
The Role
Design, build and own end to end data pipelines supporting real time and batch analytics.
Work on high volume, low latency data use cases with a strong focus on reliability and scalability.
Develop production grade data solutions using software engineering best practices such as CI/CD, testing and version control.
Contribute to the design of data models and analytics layers used across the business.
Help implement and mature staging, testing and deployment processes across the data platform.
Collaborate closely with analytics, product and engineering teams to enable better decision making.
Your Skills and Experience
Strong commercial experience as a data engineer in modern, cloud based environments.
Advanced Python and SQL, with experience using PySpark or similar distributed processing frameworks.
Experience building and maintaining data pipelines in AWS using services such as S3, Glue or EKS.
Hands on experience with modern analytics stacks such as Snowflake, dbt and Iceberg.
Familiarity with orchestration tools such as Dagster or Airflow.
Strong understanding of data modelling concepts and analytics best practice.
A software engineering mindset, including Git, testing and CI/CD workflows.
What They Offer
The chance to help shape a growing data platform and engineering culture.
Clear progression opportunities as the data team continues to expand.
Exposure to complex, real world data challenges at scale.
How to Apply
If you are a Senior Data Engineer looking to make a real impact in a growing, product led business, apply now to learn more about the opportunity.
(197990) AWS Senior Data Engineer in Crawley employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land (197990) AWS Senior Data Engineer in Crawley
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with AWS or similar tech. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines and projects. This is your chance to demonstrate your expertise in Python, SQL, and AWS services like S3 and Glue. A strong portfolio can really set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with CI/CD, testing, and version control. Practising common interview questions can help you feel more confident when it’s time to shine.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, applying directly can sometimes give you an edge over other candidates. So, what are you waiting for? Get your application in!
We think you need these skills to ace (197990) AWS Senior Data Engineer in Crawley
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Senior Data Engineer. Highlight your experience with AWS, Python, and SQL, and don’t forget to mention any relevant projects that showcase your skills in building data pipelines.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data engineering and how your background aligns with our mission at StudySmarter. Keep it concise but impactful!
Showcase Your Technical Skills: When filling out your application, be sure to highlight your technical skills, especially those related to cloud environments and modern analytics stacks. We want to see your hands-on experience with tools like PySpark, Snowflake, and CI/CD practices.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to track your application status directly. Don’t miss out on this opportunity!
How to prepare for a job interview at Harnham
✨Know Your Data Engineering Stuff
Make sure you brush up on your data engineering skills, especially in AWS. Be ready to discuss your experience with building data pipelines and using tools like S3, Glue, and EKS. They’ll want to hear about specific projects where you’ve implemented these technologies.
✨Show Off Your Python and SQL Skills
Since advanced Python and SQL are key for this role, prepare to demonstrate your proficiency. You might be asked to solve a problem or write some code on the spot, so practice common data manipulation tasks and be ready to explain your thought process.
✨Understand Their Business and Data Strategy
Research the company’s growth strategy and how data plays a role in it. Be prepared to discuss how you can contribute to their data journey and what best practices you would implement to enhance their analytics platform.
✨Be Ready to Collaborate
This role involves working closely with analytics, product, and engineering teams. Think of examples from your past experiences where you successfully collaborated across teams. Highlight your communication skills and how you can help drive better decision-making through data.