At a Glance
- Tasks: Join a dynamic team to develop and optimise data pipelines using AWS and cutting-edge technologies.
- Company: Be part of a leading consumer behaviour analytics firm shaping the future of data.
- Benefits: Enjoy hybrid working, competitive salary, and exciting referral schemes.
- Other info: Only UK residents can apply; no visa sponsorship available.
- Why this job: Challenge yourself in a collaborative environment with opportunities for growth and innovation.
- Qualifications: Proven AWS experience, strong SQL and Python skills, and familiarity with data pipeline tools required.
The predicted salary is between 48000 - 64000 £ per year.
A leader in consumer behaviour analytics seeks a driven Data Engineer with proven AWS experience to guide data infrastructure architecture, working alongside a small talented team of engineers, analysts, and data scientists. In this role, you’ll enhance the data platform, develop advanced data pipelines, and integrate cutting-edge technologies like DataOps and Generative AI, including Large Language Models (LLMs). You’ll have proven experience developing AWS Cloud platforms end to end, orchestrating data using Dagster or similar as well as coding in Python and SQL. This is an exciting opportunity for someone looking to challenge themselves in a collaborative environment, with scope to be instrumental in the scaling of the data infrastructure.
Key Responsibilities
- Develop and optimize ETL/ELT processes to support data transformation and integrity for analytics.
- Explore and evaluate new data warehousing solutions, including Snowflake, to improve data accessibility and scalability.
- Partner with product and engineering teams to define data architecture and best practices for reporting.
- Ensure data security, compliance, and governance across data systems.
- Implement and maintain CI/CD pipelines to automate data workflows and enhance system reliability.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability and performance.
Essential Skills and Experience:
- Hands-on experience with AWS services, including Lambda, Glue, Athena, RDS, and S3.
- Strong SQL skills for data transformation, cleaning, and loading.
- Strong coding experience with Python and Pandas.
- Experience of data pipeline and workflow management tools: Dagster, Celery, Airflow, etc.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- Strong communication skills to collaborate with remote teams (US, Canada).
Nice to Have
- Familiarity with LLMs including fine-tuning and RAG.
- Knowledge of Statistics.
- Knowledge of DataOps best practices, including CI/CD for data workflows.
Please note we can only accept applications from those with current UK working rights for this role; this client cannot offer visa sponsorship.
If this sounds like the role for you then please apply today!
AWS Data Engineer employer: Datatech Analytics
Datatech Analytics is an exceptional employer, offering a dynamic work culture that prioritises innovation and collaboration within the secure government and defence sectors. Employees benefit from meaningful projects that have a direct impact on national security, alongside opportunities for professional growth and development in cutting-edge technologies. With a hybrid working model and a focus on employee well-being, this role provides a unique chance to contribute to critical transformation programmes while enjoying a supportive and engaging workplace.
StudySmarter Expert Advice🤫
We think this is how you could land AWS Data Engineer
✨Tip Number 1
Familiarise yourself with the specific AWS services mentioned in the job description, such as Lambda, Glue, and S3. Having hands-on experience with these tools will not only boost your confidence but also demonstrate your capability to potential employers.
✨Tip Number 2
Engage with online communities or forums related to AWS and data engineering. Networking with professionals in the field can provide insights into the latest trends and technologies, which could be beneficial during interviews.
✨Tip Number 3
Consider working on personal projects that involve building data pipelines using Python and SQL. Showcasing these projects in discussions or interviews can highlight your practical skills and problem-solving abilities.
✨Tip Number 4
Brush up on your communication skills, especially for collaborating with remote teams. Being able to articulate your ideas clearly and effectively will be crucial in a hybrid working environment like this one.
We think you need these skills to ace AWS Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your hands-on experience with AWS services, Python, and SQL. Emphasise any relevant projects or roles where you've developed data pipelines or worked with data architecture.
Craft a Compelling Cover Letter:In your cover letter, express your enthusiasm for the role and the company. Mention specific technologies like Dagster or Snowflake that you have experience with, and how you can contribute to their data infrastructure.
Showcase Relevant Projects:If you have worked on projects involving ETL/ELT processes or CI/CD pipelines, include these in your application. Provide brief descriptions of your role and the impact of your work on data accessibility and scalability.
Highlight Communication Skills:Since the role involves collaborating with remote teams, make sure to mention any experience you have working in cross-functional teams. Highlight your communication skills and ability to work in a dynamic environment.
How to prepare for a job interview at Datatech Analytics
✨Showcase Your AWS Expertise
Make sure to highlight your hands-on experience with AWS services like Lambda, Glue, and S3. Be prepared to discuss specific projects where you utilised these tools, as this will demonstrate your capability to handle the responsibilities of the role.
✨Demonstrate Your Coding Skills
Since strong coding experience in Python and SQL is essential, be ready to talk about your previous coding projects. You might even want to prepare for a coding challenge or technical questions that assess your problem-solving skills using these languages.
✨Discuss Data Pipeline Management
Familiarise yourself with data pipeline and workflow management tools like Dagster or Airflow. Be prepared to explain how you've used these tools to optimise data workflows and ensure data integrity in past roles.
✨Emphasise Collaboration and Communication
Given the collaborative nature of the role, it's important to showcase your ability to work with cross-functional teams. Share examples of how you've effectively communicated and collaborated with remote teams, especially if you've worked with international colleagues.
