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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 data engineering with Python, SQL, and AWS services.
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 Bradford employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land (197990) AWS Senior Data Engineer in Bradford
✨Tip Number 1
Network like a pro! Reach out to people in the industry on LinkedIn or at meetups. 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 engineering projects, especially those involving AWS and modern analytics stacks. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your thought process when designing data pipelines or solving real-time analytics challenges.
✨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, 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 Bradford
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: Your cover letter is your chance to shine! Use it to explain why you’re excited about this role and how your background aligns with the company’s goals. Be genuine and let your personality come through!
Showcase Your Projects: If you've worked on any interesting data projects, make sure to mention them. Whether it's building data pipelines or using modern analytics stacks, real-world examples can really set you apart from other candidates.
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!
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
Do your homework on the company’s data journey and how it fits into their growth strategy. Being able to articulate how your skills can contribute to their goals will show that you’re genuinely interested and invested in the role.
✨Prepare Questions About Team Collaboration
Since collaboration is key in this role, think of insightful questions to ask about how the data engineering team works with analytics and product teams. This shows you’re not just focused on your own role but are also keen on contributing to the bigger picture.