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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 a collaborative culture with 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 Birmingham employer: Jefferson Frank
Contact Detail:
Jefferson Frank Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AWS Data Engineer in Birmingham
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at companies you're interested in. A friendly chat can sometimes lead to job opportunities that aren't even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your data projects, especially those involving AWS, SQL, and Python. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your past projects and how you've tackled challenges, especially in relation to AWS and data pipelines.
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications directly from candidates who are excited about joining us. Plus, it shows your enthusiasm for the role and the company.
We think you need these skills to ace AWS Data Engineer in Birmingham
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of AWS Data Engineer. Highlight your experience with SQL, Python, and AWS Redshift, 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. Be genuine and let your personality come through!
Showcase Relevant Projects: If you've worked on projects that involved building data pipelines or improving data quality, make sure to include them in your application. We love seeing real-world examples of your work and how you’ve tackled challenges in the past.
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 the role. Plus, it shows us you’re keen to join our team!
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 on the spot, so practice writing queries that involve data manipulation and aggregation. Highlight any specific projects where your SQL skills made a significant impact.
✨Talk About Team Collaboration
Since this role involves partnering with Engineering and DevOps, be ready to share examples of how you've successfully collaborated with other teams. Discuss any tools or processes you used to ensure smooth data workflows and how you handled any conflicts or challenges.
✨Emphasise Data Quality and Compliance
Data quality and compliance are crucial in this role. Be prepared to discuss your approach to ensuring data integrity and how you’ve aligned your practices with GDPR and security standards in previous roles. This will show that you understand the importance of these aspects in a data engineering context.