At a Glance
- Tasks: Design and build Python libraries for data transformation using YAML files.
- Company: Join a dynamic team working on a UK government account.
- Benefits: Competitive daily rate, fully remote work, and opportunity to work on impactful projects.
- Other info: Must hold SC clearance and be UK based.
- Why this job: Make a difference in data engineering while working with cutting-edge technologies.
- Qualifications: Expertise in Python, Pyspark, and strong knowledge of Databricks required.
Data Engineer required with SC clearance to work on a UK government account. Must be UK based and hold a valid and current passport.
Technology requirements:
- Python 3 / Pyspark 3/4
- Python behave - for Behaviour Driven Development and testing
- Python coverage - Code coverage
- Strong knowledge of Databricks, including delta parquet data format and the medallion data architecture
- Strong knowledge of YAML
- Understanding of Azure Devops
- Understanding of Git and code release best practices
The role will be to design and build core python libraries for ingesting various data sets. The overarching concept of this solution is that the libraries will utilise YAML files to control the transformation of all data sets. Therefore, for each different data set, the engineers will be required to create appropriate YAML files and utilise the libraries that will be created here without specific python programming.
As well as strong Python and programming experience, the resource will also need to create the YAML files for converting the incoming data into the appropriate Bronze/Silver/Gold medallion architecture and create behaviour driven tests using Python Behave. All development will be released through Azure Devops pipelines, that will be created by a separate team, but an understanding of the technology and knowledge of Git best practices would be an advantage.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer in Northampton
✨Showcase Your Skills with a Public Portfolio
As a freelancer in data science, having a killer portfolio is essential. Showcase your projects on platforms like GitHub or create a personal website that details your work and techniques. This gives potential clients a clear picture of what you can do and helps you stand out from the competition.
✨Get Involved in Data Science Communities
Tap into online forums like Kaggle or Stack Overflow. Not only can you showcase your expertise, but you can also connect with other data scientists and potential clients. Plus, participating in competitions and discussions can elevate your profile in the field.
✨Leverage Local Networking Opportunities
Keep an eye out for local data science meetups or tech events in your area. These are golden opportunities to meet potential clients and collaborators face-to-face. Plus, who doesn't love a bit of networking over pizza and drinks?
✨Pitch Your Services Directly to Companies
Don't just wait for freelancing platforms to bring clients to you—be proactive! Research companies that could benefit from data science services and craft tailored pitches. Mention specific pain points you can address for them. Let’s get that freelance hustle going!
We think you need these skills to ace Data Engineer in Northampton
Some tips for your application 🫡
Showcase Your Projects:When applying for a freelance data science role like Data Engineer at BrightBox Group, it’s crucial to highlight your projects. Include a portfolio that features at least two or three projects involving data analysis, machine learning, or visualisation. Make sure to describe the tools and methodologies you used, so we can see your skills in action!
Quantify Your Achievements:Freelance gigs, especially in data science, often ask for proven results. In your CV, include any relevant metrics or outcomes from your previous work. Did your analysis help reduce costs by a certain percentage? Or did your predictive model improve performance? Numbers speak volumes!
Introduce Your Style:Since freelancing is all about your individual style and approach, use your cover letter to share how you tackle data problems. This is your chance to let us know how you think, your creative problem-solving methods, and how you would approach a project at BrightBox Group.
Be Real About Your Rates:When you send in your application, don’t forget to mention your freelance rates and availability. We appreciate clarity up front, and it helps us gauge if you fit within our budget and timeline. Being transparent in this aspect shows professionalism and readiness!
How to prepare for a job interview at BrightBox Group
✨Show Off Your Data Wizardry
As a freelancer in data science, you'll want to present a portfolio that showcases your best projects. We should pull together examples where you tackled real problems with data analytics, machine learning models, or visualisations. It's all about demonstrating your skills in action!
✨Be Ready to Dive Deep into Technical Questions
Expect to encounter some technical grilling during the interview. Prepare to discuss statistical methods, algorithms, or maybe even tackle a live coding challenge. We should brush up on tools like Python, R, or SQL—those are key players in the data science field. Don't just know them; be ready to explain your thought process!
✨Help Them Understand Your Work Style
Freelance gigs often mean you'll be working independently, so we need to convey our self-motivation and time management skills. Be prepared to talk about how you’ve handled multiple projects or met tight deadlines before. Sharing your approach to client communication can also give them confidence in your ability to deliver remotely.
✨Pitch Your Value Proposition
When freelancing, it’s crucial to clearly articulate what makes you unique. We should highlight not just technical skills but also the business impact of our projects. Think of a couple of stories where your data insights drove decision-making—this can be a game changer in showing why they should choose you for their freelance needs!
