At a Glance
- Tasks: Build scalable data pipelines and automate workflows using AWS, Databricks, and PySpark.
- Company: Join a high-impact engineering team in a collaborative environment.
- Benefits: Competitive salary of £80k-£95k, hybrid work model, and career growth opportunities.
- Other info: Start in August and enjoy a dynamic workplace in London or Glasgow.
- Why this job: Work with cutting-edge technology and make a real impact on marketing insights.
- Qualifications: Experience in cloud environments, AWS services, and strong skills in PySpark and SQL.
The predicted salary is between 80000 - 90000 £ per year.
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 Oldham 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 data solutions in a hybrid environment that balances flexibility with collaboration. With a strong focus on employee growth, our company offers extensive training and development opportunities, alongside a supportive work culture that values creativity and teamwork. Located in vibrant Central London or Glasgow, you will enjoy the unique advantages of these thriving cities while contributing to impactful projects that drive real business insights.
StudySmarter Expert Advice🤫
We think this is how you could land Remote Senior Data Engineer - AWS/Databricks/PySpark - August Start Date in Oldham
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like WüNDER_TALENT!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Remote Senior Data Engineer - AWS/Databricks/PySpark - August Start Date at WüNDER_TALENT.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like WüNDER_TALENT.
✨Apply Directly through Our Website
When you find a suitable opening like Remote Senior Data Engineer - AWS/Databricks/PySpark - August Start Date at WüNDER_TALENT, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Remote Senior Data Engineer - AWS/Databricks/PySpark - August Start Date in Oldham
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at WüNDER_TALENT, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at WüNDER_TALENT. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at WüNDER_TALENT
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at WüNDER_TALENT!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
