At a Glance
- Tasks: Build scalable data pipelines and automate workflows using cutting-edge tools.
- Company: Join a high-impact engineering team in a collaborative environment.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Exciting opportunity to start in August with excellent career development prospects.
- Why this job: Work with advanced technologies and make a real impact on marketing insights.
- Qualifications: Experience in cloud environments and strong skills in AWS, PySpark, and Databricks.
Location: This is a hybrid engagement represented by 2 days/week onsite, either in Central London or Glasgow.
Start Date: Must be able to start mid-August.
Salary: £80k-£90k (Senior) | £90k-£95k (Lead)
About The Role
Our partner is looking for a Senior Data Engineer to join a high-impact engineering team delivering scalable data solutions for complex marketing and customer insight use cases. This is an opportunity to work on cutting-edge data pipelines, cloud-native platforms and real-time data flows in a collaborative, forward-thinking environment. You’ll be involved in designing and building production-grade ETL pipelines, driving DevOps practices across data systems and contributing to high-availability architectures using tools like Databricks, Spark and Airflow - all within a modern AWS ecosystem.
Responsibilities
- Architect and build scalable, secure data pipelines using AWS, Databricks and PySpark.
- Design and implement robust ETL/ELT solutions for both structured and unstructured data.
- Automate workflows and orchestrate jobs using Airflow and GitHub Actions.
- Integrate data with third-party APIs to support real-time marketing insights.
- Collaborate closely with cross-functional teams including Data Science, Software Engineering and Product.
- Champion best practices in data governance, observability and compliance.
- Contribute to CI/CD pipeline development and infrastructure automation (Terraform, AWS DevOps).
- Provide input into technical decisions, peer reviews and solution design.
Requirements
- Proven experience as a Data Engineer in cloud-first environments.
- Strong commercial knowledge of AWS services (e.g. S3, Glue, Redshift).
- Advanced PySpark and Databricks experience (Delta Lake, Unity Catalog, Databricks Jobs etc).
- Proficient in SQL (T-SQL/SparkSQL) and Python for data transformation and scripting.
- Hands-on experience with workflow orchestration tools such as Airflow.
- Strong version control and DevOps exposure (Git, GitHub Actions, Terraform).
- Familiar with data quality tools and metadata/cataloguing (e.g. Great Expectations, Unity Catalog).
Beneficial: MarTech domain knowledge.
Remote Senior Data Engineer - AWS/Databricks/PySpark - August Start Date in Swansea employer: WüNDER_TALENT
Join a dynamic and innovative team as a Senior Data Engineer, where you'll have the opportunity to work on cutting-edge technologies in a hybrid environment that promotes collaboration and flexibility. With a strong focus on employee growth, our company offers extensive training and development opportunities, ensuring you stay at the forefront of the data engineering field. Enjoy a supportive work culture that values creativity and teamwork, all while being based in vibrant locations like Central London or Glasgow.
StudySmarter Expert Advice🤫
We think this is how you could land Remote Senior Data Engineer - AWS/Databricks/PySpark - August Start Date in Swansea
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with AWS, Databricks, or PySpark. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving ETL pipelines and cloud-native solutions. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common data engineering scenarios and be ready to discuss how you've tackled challenges in past projects.
✨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 Remote Senior Data Engineer - AWS/Databricks/PySpark - August Start Date in Swansea
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with AWS, Databricks, and PySpark. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
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 you can contribute to our high-impact engineering team. Keep it concise but engaging!
Showcase Your Technical Skills:When filling out your application, be specific about your technical expertise. Mention your hands-on experience with ETL pipelines, Airflow, and any other tools listed in the job description. We love details!
Apply Through Our Website:We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at WüNDER_TALENT
✨Know Your Tech Stack
Make sure you brush up on your AWS, Databricks, and PySpark knowledge. Be ready to discuss specific projects where you've used these technologies, as well as any challenges you faced and how you overcame them.
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've designed and built ETL pipelines in the past. Use examples that highlight your ability to handle both structured and unstructured data, and be ready to explain your thought process during the design phase.
✨Collaboration is Key
Since this role involves working closely with cross-functional teams, think of examples that demonstrate your teamwork skills. Be prepared to discuss how you've collaborated with Data Science or Software Engineering teams to achieve common goals.
✨DevOps and Automation Experience
Familiarise yourself with CI/CD practices and tools like Terraform and GitHub Actions. Be ready to share your experiences in automating workflows and orchestrating jobs, as this will show your understanding of modern data engineering practices.
