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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 and SQL skills.
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 Aberdeen employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land (197990) AWS Senior Data Engineer in Aberdeen
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with AWS. A friendly chat can lead to insider info about job openings or even referrals.
✨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.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering scenarios. Be ready to discuss how you've tackled real-time analytics challenges and implemented CI/CD practices in your previous roles.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace (197990) AWS Senior Data Engineer in Aberdeen
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experience mentioned in the job description. Highlight your AWS, Python, and SQL expertise, and don’t forget to showcase any relevant projects that demonstrate your data engineering prowess.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you’re the perfect fit for this role. Share your passion for data engineering and how your previous experiences align with our mission to build a high-performing data platform.
Showcase Your Projects: If you've worked on any interesting data projects, make sure to mention them! We love seeing real-world applications of your skills, especially if they involve modern tools like Snowflake or orchestration tools like Airflow.
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 to join our growing team!
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, Python, and SQL. Be ready to discuss your experience with building data pipelines and using tools like Glue or EKS. They’ll want to see that you can handle real-time analytics and understand the importance of reliability and scalability.
✨Show Off Your Problem-Solving Skills
Prepare to talk about specific challenges you've faced in previous roles and how you tackled them. Think about examples where you improved data processes or implemented CI/CD practices. This is your chance to demonstrate your software engineering mindset and how you can contribute to their data platform.
✨Get Familiar with Their Tech Stack
Do some homework on the tools mentioned in the job description, like Snowflake, dbt, and orchestration tools like Airflow or Dagster. Being able to discuss these technologies will show that you're not just a fit for the role but also genuinely interested in their operations.
✨Ask Insightful Questions
Prepare thoughtful questions about their data journey and how the team collaborates across different functions. This shows that you’re engaged and eager to contribute to their growth strategy. Plus, it gives you a better understanding of what working there would be like!