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For Companies At a Glance
- Tasks: Design and develop scalable data solutions using Python and AWS services.
- Company: Leading IT solutions provider in the UK and EU market.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Join a dynamic team to build next-gen data platforms and make an impact.
- Qualifications: 10+ years of experience in data engineering and strong Python skills.
- Other info: Collaborative Agile environment with a focus on innovation and excellence.
The predicted salary is between 43200 - 72000 £ per year.
We provide end-to-end IT solutions and services including Applications services, Data & Analytics services, AI/ML Technologies and Professional services in the UK and EU market.
Role Overview
We are building a next-generation data platform and are looking for an experienced Senior Data Engineer to help design, develop, and optimize large-scale data solutions. This role involves end-to-end data engineering, modern cloud-based development, and close collaboration with cross-functional stakeholders to deliver reliable, scalable, and high-quality data products.
Key Responsibilities
- Design, develop, and maintain scalable, testable, and high-performance data pipelines using Python and Apache Spark.
- Orchestrate data workflows using cloud-native services such as AWS Glue, EMR Serverless, Lambda, and S3.
- Apply modern engineering practices including modular design, version control, CI/CD automation, and comprehensive testing.
- Support the design and implementation of lakehouse architectures leveraging table formats such as Apache Iceberg.
- Collaborate with business stakeholders to translate requirements into robust data engineering solutions.
- Build observability and monitoring into data workflows; implement data quality checks and validations.
- Participate in code reviews, pair programming, and architecture discussions to promote engineering excellence.
- Continuously expand domain knowledge and contribute insights relevant to data operations and analytics.
What You’ll Bring
- Strong ability to write clean, maintainable Python code using best practices such as type hints, linting, and automated testing frameworks (e.g., pytest).
- Deep understanding of core data engineering concepts including ETL/ELT pipeline design, batch processing, schema evolution, and data modeling.
- Hands-on experience with Apache Spark or willingness and capability to learn large-scale distributed data processing.
- Familiarity with AWS data services such as S3, Glue, Lambda, and EMR.
- Ability to work closely with business and technical stakeholders and translate needs into actionable engineering tasks.
- Strong team collaboration skills, especially within Agile environments, emphasizing shared ownership and high transparency.
Nice-to-Have Skills
- Experience with Apache Iceberg or similar lakehouse table formats (Delta Lake, Hudi).
- Practical exposure to CI/CD tools such as GitLab CI, GitHub Actions, or Jenkins.
- Familiarity with data quality frameworks such as Great Expectations or Deequ.
- Interest or background in financial markets, analytical datasets, or related business domains.
AWS Data Engineer employer: Technopride Ltd
Contact Detail:
Technopride Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AWS Data Engineer
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who’s already in the field. Building relationships can open doors that a CV just can’t.
✨Show Off Your Skills
Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your projects, especially those involving AWS services or data pipelines. This gives potential employers a taste of what you can do.
✨Ace the Interview
Prepare for technical interviews by brushing up on your Python and Apache Spark skills. Practice common data engineering problems and be ready to discuss your past projects in detail. Confidence is key!
✨Apply Through Us
Make sure to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it helps us keep track of your application and get back to you faster.
We think you need these skills to ace AWS Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AWS Data Engineer role. Highlight your experience with Python, Apache Spark, and AWS services. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how you can contribute to our next-generation data platform. Keep it engaging and relevant!
Showcase Your Projects: If you've worked on any relevant projects, make sure to mention them! Whether it's building data pipelines or using cloud-native services, we love seeing real-world examples of your work.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you'll be one step closer to joining our awesome team at StudySmarter!
How to prepare for a job interview at Technopride Ltd
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python, Apache Spark, and AWS services. Brush up on your knowledge of data pipelines and cloud-native services like AWS Glue and Lambda, as these will likely come up during technical discussions.
✨Showcase Your Projects
Prepare to discuss specific projects where you've designed and developed data solutions. Highlight your role in building scalable data pipelines and any challenges you overcame. This not only demonstrates your experience but also your problem-solving skills.
✨Understand the Business Context
Familiarise yourself with the company’s industry and how data engineering plays a role in their operations. Be ready to discuss how you can translate business requirements into technical solutions, showing that you can bridge the gap between stakeholders and engineering.
✨Emphasise Collaboration
Since this role involves working closely with cross-functional teams, be prepared to talk about your experience in Agile environments. Share examples of how you’ve collaborated with others, participated in code reviews, or contributed to team discussions to promote engineering excellence.
