At a Glance
- Tasks: Join our team to build innovative data solutions on Google Cloud Platform.
- Company: Dynamic tech company focused on cutting-edge data engineering.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Work in a collaborative environment with excellent career advancement opportunities.
- Why this job: Make a real impact by developing AI-enabled data products and leading feature teams.
- Qualifications: Expertise in GCP, dbt, Python, SQL, and strong data modelling skills required.
The predicted salary is between 59400 - 72600 £ per year.
In-scope technologies/products:
- Google Cloud Platform (GCP) and comparable cloud-based data engineering services
- dbt
- Python
- SQL
- ETL/ELT tooling and methodologies
- Data modelling and data product development
- AI-enabled data development
- Testing and validation frameworks
- Master Data Management (MDM), including commercial off-the-shelf and bespoke solutions
- MDM integration and implementation
- Real-time data product patterns
- DevOps tooling and deployment practices
Skillsets required:
- Expert-level GCP or cloud-based data engineering capability
- Advanced practical experience of dbt, Python data engineering and SQL
- Strong data modelling and ETL/ELT design skills
- Proven end-to-end data product build experience
- Experience applying AI-enabled approaches to data development
- Strong testing, data validation and quality assurance capability
- Data architecture expertise
- MDM and enterprise data architecture experience, including strategy, solution selection, integration and implementation
- DevOps, deployment, governance, and production go-live experience
- Senior technical leadership capable of leading a multidisciplinary feature team
Scope of services:
The requirement is for two UK-based feature teams, each comprising six resources and led by a Senior Lead Data Engineer. All team members must be based in Bristol or Manchester; London-based delivery is specifically excluded. The teams are required to start immediately, and suppliers must propose resources who are available and capable of being onboarded without delay.
- Improve the quality, richness, and consumption-readiness of FDP data.
- Deliver FDPs end to end, from ODP selection through design, engagement and shaping, development, DevOps, testing, validation, governance, deployment and go-live.
- Define and support MDM architecture and strategy.
- Assess and implement commercial off-the-shelf MDM products where appropriate.
- Design and develop bespoke MDM solutions.
- Deliver MDM integration and implementation activities.
- Design and implement real-time data product patterns.
- Work within the applicable delivery, architecture, engineering, security and governance standards.
- Provide experienced, delivery-ready practitioners; proposals based on academic exercises, speculative hiring or resources requiring extended mobilisation will not be accepted.
GCP Data Engineer in Bristol employer: Test Triangle
As a Project Lead L1 at our esteemed global investment banking client, you will thrive in a dynamic work culture that prioritises innovation and collaboration. We offer competitive benefits, including professional development opportunities and a supportive environment that encourages growth and advancement within the financial sector. Join us in a location that fosters both personal and professional fulfilment, where your contributions directly impact large-scale technology transformations.
StudySmarter Expert Advice🤫
We think this is how you could land GCP Data Engineer in Bristol
✨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 Test Triangle.
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We think you need these skills to ace GCP Data Engineer in Bristol
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 Test Triangle, 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 Test Triangle. 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 Test Triangle
✨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 Test Triangle!
✨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.
