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For Companies At a Glance
- Tasks: Build and enhance data pipelines, support analytics, and contribute to ML/AI initiatives.
- Company: Rapidly growing tech scale-up with a focus on data-driven innovation.
- Benefits: 25 days annual leave, stock options, remote work, and career development opportunities.
- Why this job: Join a dynamic team and shape the future of data in a high-impact role.
- Qualifications: Strong SQL and Python skills, experience with AWS Redshift and dbt.
- Other info: Enjoy regular team socials and 24/7 wellbeing support.
The predicted salary is between 48000 - 72000 £ per year.
An exciting, high-growth technology scale-up is seeking a Data Engineer to help evolve and strengthen its modern data foundations. This organisation builds a global, API-first platform used by major enterprise brands to improve data quality, automate workflows, and enhance the reliability of their marketing and operational data. This is a fantastic opportunity to join a business experiencing rapid expansion, where data is central to product innovation, analytics, machine learning, and AI initiatives. You will work with modern tooling, collaborate closely with Engineering and DevOps, and help shape a robust, scalable data ecosystem.
The Role
As a Data Engineer, you will play a key role in building and improving data pipelines, increasing access to platform and event data, and developing reliable, reusable datasets that support analytics and data-driven decision-making. You’ll take ownership of evolving the company's AWS-based data infrastructure and contribute directly to high-impact initiatives across analytics, ML, and AI.
Key Responsibilities:
- Build, maintain and enhance data pipelines from operational systems into analytics platforms
- Partner with Engineering & DevOps to support ingestion, replication and platform data flows
- Define data storage strategy and manage data in AWS S3
- Build analytics-ready datasets in AWS Redshift, using dbt for transformation
- Improve data quality, monitoring and documentation across the data stack
- Support ML/AI initiatives with clean, well-structured datasets
- Ensure data practices align with GDPR, security and compliance standards
Experience Required
- Strong SQL skills and experience working with AWS Redshift
- Strong Python experience for production data pipelines
- Hands-on experience with dbt for modelling and transformations
- Familiarity with AWS services
- Comfortable partnering with Engineering and DevOps on data workflows
- Understanding of version control and CI/CD best practices
Benefits:
- 25 days' annual leave and your birthday off
- Stock options eligibility
- Remote working
- Career development opportunities in a scaling tech environment
- Employee Assistance Programme – 24/7 wellbeing support
- Regular team socials and events
- Pension plan
AWS Data Engineer in Manchester employer: Jefferson Frank
Contact Detail:
Jefferson Frank Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AWS Data Engineer in Manchester
✨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, especially those involving AWS, SQL, and Python. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your thought process when building data pipelines or working with AWS services, as this will help you stand out during technical interviews.
✨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 AWS Data Engineer in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Data Engineer. Highlight your experience with AWS, SQL, and Python, and don’t forget to mention any hands-on work with dbt. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you’re excited about this opportunity and how your background makes you a perfect fit for our team. Keep it engaging and relevant to the job description.
Showcase Your Projects: If you've worked on any cool data projects, make sure to include them! Whether it's building data pipelines or working with analytics platforms, we love to see real examples of your work that demonstrate your skills.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Jefferson Frank
✨Know Your AWS Inside Out
Make sure you brush up on your AWS knowledge, especially around services like S3 and Redshift. Be ready to discuss how you've used these tools in past projects, as well as any challenges you faced and how you overcame them.
✨Show Off Your SQL Skills
Prepare to demonstrate your SQL prowess during the interview. You might be asked to solve a problem or optimise a query on the spot, so practice common SQL scenarios and be ready to explain your thought process.
✨Talk About Data Pipelines
Be prepared to discuss your experience with building and maintaining data pipelines. Share specific examples of how you've improved data quality or streamlined workflows, and highlight any collaboration with Engineering and DevOps teams.
✨Understand GDPR and Compliance
Since data practices must align with GDPR and compliance standards, make sure you can articulate your understanding of these regulations. Discuss how you've implemented data governance in previous roles to ensure data security and compliance.