Remote Senior Data Engineer - AWS/Databricks/PySpark - August Start Date in Huddersfield
About the role
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.
Your tasks
Build scalable data pipelines and automate workflows using cutting-edge tools.
Your profile
Experience in cloud environments, AWS, PySpark, and data engineering.
What's also included
Competitive salary, hybrid work model, and opportunities for professional growth.
Tech stack & ways of working
Remote Senior Data Engineer - AWS/Databricks/PySpark - August Start Date in Huddersfield employer: WüNDER_TALENT
Join a forward-thinking tech-driven organisation that values innovation and data-driven decision-making. As a Senior Data Analyst, you'll enjoy a flexible remote work environment in the UK, competitive salary up to £70k, and opportunities for professional growth through mentorship and collaboration on impactful projects. Embrace a culture that encourages continuous learning and empowers you to shape the data strategy while working with cutting-edge technologies like Snowflake, SQL, and Python.
Your perspectives
Work with advanced technologies and make a real impact on marketing insights.
StudySmarter Expert Advice
Get Involved in Data Science Meetups
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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.
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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!
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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!
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Get Comfortable with Python and R
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Prepare for Case Studies
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Locations
- Huddersfield
