At a Glance
- Tasks: Lead the transformation of complex data pipelines using AWS and PySpark.
- Company: Join a global tech leader driving innovative cloud data solutions.
- Benefits: Competitive daily rate, flexible contract, and collaborative work environment.
- Other info: Opportunity for significant career growth in a dynamic, tech-driven culture.
- Why this job: Shape the future of data engineering and influence multiple teams.
- Qualifications: Experience in Data Engineering with Python, AWS, and modern data architectures.
The predicted salary is between 63000 - 77000 £ per year.
Staff Data Engineer | AWS | Py Spark | Data Modernisation | London | Contract | Inside IR35
We're supporting a global, technology-led organisation undertaking a large-scale cloud data transformation programme.
This isn't a traditional Data Engineering role.
The organisation is modernising hundreds of complex data pipelines, establishing reusable engineering patterns and embedding engineering excellence across its Data function.
As a Staff-level engineer, you'll combine deep hands-on technical expertise with organisation-wide technical influence, helping shape how modern Data Engineering is delivered across multiple engineering teams.
This is an opportunity to work on enterprise-scale data movement, cloud-native architectures and AI-assisted software engineering within a highly collaborative engineering culture.
Responsibilities
- Defining technical standards and engineering patterns for a large-scale Data Modernisation programme
- Re-engineering complex legacy data pipelines into production-grade Py Spark
- Building scalable, reusable data movement frameworks across multiple engineering teams
- Driving best practice around AWS Glue, Apache Spark and Apache Airflow
- Designing high-quality testing frameworks covering performance, data quality and reliability
- Leveraging Agentic AI development tools to improve engineering productivity while maintaining code quality
- Coaching and influencing experienced engineers through technical leadership rather than line management
- Working closely with enterprise architecture and platform teams to improve how data is governed, managed and consumed
Experience required
- Staff, Principal or Lead Data Engineering roles
- Python and expert-level Py Spark
- AWS Glue
- Apache Spark
- Apache Airflow
- Cloud-native Data Engineering architectures
- Large-scale data pipeline modernisation
- Building reusable engineering patterns within enterprise environments
- Data testing, validation and observability
- AI-assisted software development using modern coding assistants
- Working within regulated or highly governed organisations
- Contract
- £750-900 per day (inclusive)
- Initial 6-month contract with significant programme runway
- Inside IR35
- London (3 days per week on-site)
- #J-18808-Ljbffr
Staff Data Engineer | London | Contract | Inside IR35 employer: WeDo
Join a dynamic and growing Microsoft Partner in the Midlands or South, where your role as an Account Manager will focus on building meaningful, long-term relationships with customers. Enjoy a supportive work culture that values collaboration and invests in employee growth, offering hybrid working options and a competitive salary package that includes a car allowance and commission. This is a unique opportunity to make a significant impact in a company that prioritises customer success and values your contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Data Engineer | London | Contract | Inside IR35
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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 WeDo.
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We think you need these skills to ace Staff Data Engineer | London | Contract | Inside IR35
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 WeDo, 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 WeDo. 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 WeDo
✨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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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 WeDo!
✨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.
