At a Glance
- Tasks: Join a dynamic team to improve data processes in a government setting.
- Company: Independent digital transformation consultancy with diverse clients.
- Benefits: Competitive pay, flexible working, and opportunities for professional growth.
- Other info: Work one day a week in London with a focus on collaboration.
- Why this job: Make a real difference by solving complex data challenges.
- Qualifications: Experience in data engineering, especially within government frameworks.
The predicted salary is between 50000 - 60000 £ per year.
We're an independent digital transformation consultancy with clients across public and private sectors. We help our clients solve complex technical problems and provide human‑centred solutions that lead to positive outcomes. We do this with multidisciplinary teams of strategists, architects, developers, designers and analysts working closely alongside client stakeholders and end users.
The Role
We're looking for a hands‑on Data Engineer to work on a programme of improvement and remediation to close data gaps within a government department. You'll be a strong communicator, with experience of delivering products and services in a Government environment. This includes engaging with stakeholders, ensuring the right structures and processes are in place to effectively capture, monitor and remediate data issues. This is a hands-on technical role as part of the project team. You'll be confident working with data on large and complex platforms with multiple data ingestion points. You'll access and query the data and be able to implement methods to transform and transfer data. You'll be able to discuss options and approaches with the project team. You'll have a strong understanding of data quality principles (accuracy, completeness, consistency, timeliness, validity) and the ability to work in an agile environment.
Experience and Competencies
- GDS Standards: Recent experience working within the Government Digital Service framework, ensuring data services are accessible, secure, and user‑centric. Providing technical input to use cases and problem statements is essential.
- Agile Delivery: Experienced in Scrum/Kanban environments, participating in ceremonies (Dailies, Refinement, Retrospectives) and managing tasks via backlogs.
- Data Engineering Best Practices: Knowledge of ETL/ELT patterns, data versioning, and building robust, automated pipelines. You'll ensure data security and compliance requirements are met with solutions you propose and build.
- Streamlining Data Flows: Able to identify and implement process improvements for better data handling.
- Collaboration: Ability to work closely with Business Analysts, Data Analysts and business stakeholders to translate requirements into technical specifications.
Technical Experience and Tooling
- Cloud Platform: Proven experience working with AWS and data warehousing.
- Programming: Advanced proficiency in Python and R for data manipulation and automation.
- Database: Expert‑level SQL for complex querying and data modelling. Use of dbt to utilise SQL in a data warehouse.
- Orchestration & Containers: Practical experience with Kubernetes and use of pipelines for deploying and scaling data services.
Working Arrangements
One day in the London office per week. Arrangements may vary based on project and team needs. Active SC clearance required.
Data Engineer (SC Cleared) employer: 慨正橡扯
As an independent digital transformation consultancy, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to tackle complex challenges in both public and private sectors. With a strong focus on professional development, we offer numerous growth opportunities and encourage our team members to engage with multidisciplinary experts, ensuring a rewarding experience while working on impactful government projects in the heart of London.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer (SC Cleared)
✨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 (SC Cleared)
Some tips for your application 🫡
Showcase Your Projects:When applying for a freelance data science role like Data Engineer (SC Cleared) at 慨正橡扯, 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 慨正橡扯.
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 慨正橡扯
✨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!
