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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.
Remote UK, £90,000 to £100,000
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 employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land (197990) AWS Senior Data Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving AWS, Python, and SQL. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your thought process and how you've tackled challenges in past projects—this is your chance 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, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace (197990) AWS Senior Data Engineer
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 experience, data engineering projects, and any relevant tools you've used. We want to see how you can contribute to our data journey!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data engineering and how you can help shape our growing data platform. Be sure to mention specific examples of your work that align with our needs.
Showcase Your Technical Skills: Since we're all about modern tooling and best practices, make sure to highlight your proficiency in Python, SQL, and any cloud-based environments you've worked with. We love seeing hands-on experience with AWS services like S3 and Glue!
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. Don’t miss out on the chance to join our team!
How to prepare for a job interview at Harnham
✨Know Your Data Tools
Make sure you’re well-versed in the tools mentioned in the job description, like AWS services, PySpark, and Snowflake. Brush up on your knowledge of data pipelines and be ready to discuss how you've used these technologies in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled complex data challenges. Think about times when you improved data reliability or scalability, and be ready to explain your thought process and the impact of your solutions.
✨Understand the Company’s Data Vision
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 align your skills with their goals, showing that you’re genuinely interested in their mission.
✨Collaborate and Communicate
Since the role involves working closely with analytics, product, and engineering teams, practice articulating your ideas clearly. Prepare to discuss how you’ve collaborated in the past and how you can facilitate better decision-making through effective communication.