At a Glance
- Tasks: Lead data-driven solutions using Google Cloud tools and mentor a dynamic engineering team.
- Company: PA Consulting, a forward-thinking firm in Bristol with a focus on innovation.
- Benefits: Competitive salary, private medical insurance, generous leave, and performance bonuses.
- Other info: Embrace a culture of diversity and continuous learning while driving technological advancements.
- Why this job: Join a collaborative environment where your expertise shapes impactful data solutions.
- Qualifications: Experience with GCP, data processing, and strong communication skills are essential.
The predicted salary is between 70000 - 90000 £ per year.
Firm: PA Consulting
Job Description
As a Principal GCP Data Engineer, you'll be a true subject‑matter expert in using the data processing and management capabilities of Google Cloud to develop data‑driven solutions for our clients.
You will typically lead a team or the solution delivery effort, demonstrating technical excellence through leading by example.
You could be providing technical support, leading an engineering team or working across multiple teams as a subject‑matter expert who is critical to the success of a large programme of work.
Responsibilities
- Develop robust data processing jobs using tools such as Google Cloud Dataflow, Dataproc and Big Query
- Design and deliver automated data pipelines that use orchestration tools such as Cloud Composer
- Design end‑to‑end solutions and contribute to architecture discussions beyond data processing
- Own the development process for your team, building strong principles and putting robust methods and patterns in place across architecture, scope, code quality and deployments.
- Shape team behaviour for writing specifications and acceptance criteria, estimating stories, sprint planning and documentation.
- Actively define and evolve PA’s data engineering standards and practices, ensuring we maintain a shared, modern and robust approach.
- Lead and influence technical discussions with client stakeholders to achieve the collective buy‑in required to be successful.
- Coach and mentor team members, regardless of seniority, and work with them to build their expertise and understanding.
Qualifications
- Experience delivering and deploying production‑ready data processing solutions using Big Query, Pub/Sub, Dataflow and Dataproc
- Experience developing end‑to‑end solutions using batch and streaming frameworks such as Apache Spark and Apache Beam.
- Expert understanding of when to use a range of data storage technologies including relational/non‑relational, document, row‑based/columnar data stores, data warehousing and data lakes.
- Expert understanding of data pipeline patterns and approaches such as event‑driven architectures, ETL/ELT, stream processing and data visualisation.
- Experience working with business owners to translate business requirements into technical specifications and solution designs that satisfy the data requirements of the business.
- Experience working with metadata management products such as Cloud Data Catalog and Collibra and Data Governance tools like Dataplex.
- Experience in developing solutions on GCP using cloud‑native principles and patterns.
- Experience building data quality alerting and data quarantine solutions to ensure downstream datasets can be trusted.
- Experience implementing CI/CD pipelines using techniques including Git code control/branching, automated tests and automated deployments.
- Comfortable working in an Agile team using Scrum or Kanban methodologies.
- Preferred Experience
- Experience of working on migrations of enterprise‑scale data platforms including Hadoop and traditional data warehouses
- An understanding of machine learning model development lifecycle, feature engineering, training and testing
- Good understanding or hands‑on experience of Kafka
- Experience as a DBA or developer on RDBMS such as Postgre SQL, My SQL, Oracle or SQL Server
- Experience designing data applications to meet non‑functional requirements such as performance and availability
- Personal Qualities
- You are pragmatic and already understand that writing code is only part of what a data engineer does.
- You can clearly communicate with both clients and peers, describing technical issues and solutions in both written and meeting/workshop contexts.
- You are able to clearly explain technical concepts to non‑technical audiences at all levels of an organisation.
- You are able to influence and persuade senior and specialist client stakeholders, potentially across multiple organisational boundaries without direct authority.
- You are a confident problem solver and troubleshooter.
- You are confident and generous in sharing your specialist knowledge, ideas and solutions.
- You are constantly learning and able to make others better by consciously teaching and unconsciously inspiring.
Benefits
- Competitive
- Private medical insurance
- Interest free season ticket loan
- 25 days annual leave with the opportunity to buy 5 additional days
- Company pension scheme
- Annual performance‑based bonus
- Life and income protection insurance
- Tax‑efficient benefits (cycle to work, give as you earn, childcare benefits)
- Voluntary benefits (Dental, critical illness, spouse/partner life assurance)
PA is committed to building an inclusive and supportive culture where diversity thrives, and all of our people can excel.
We believe that greater diversity stimulates innovation, enabling us to fulfil our purpose of ‘Bringing Ingenuity to Life’, supporting the growth of our people, and delivering more enduring results for our clients.
#J-18808-Ljbffr
Google Cloud Platform Data Engineer in England employer: Consultancy.uk
Campbell Tickell is an excellent employer, offering a dynamic work culture that values innovation and collaboration in the heart of Central London. Employees benefit from competitive salaries, a generous bonus structure, and ample opportunities for professional growth through impactful consultancy projects in the public and social sectors. Join a team that is dedicated to making a difference while enjoying the vibrant lifestyle that London has to offer.
StudySmarter Expert Advice🤫
We think this is how you could land Google Cloud Platform Data Engineer in England
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Consultancy.uk!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Google Cloud Platform Data Engineer at Consultancy.uk.
✨Leverage Professional Networks
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 Consultancy.uk.
✨Apply Directly through Our Website
When you find a suitable opening like Google Cloud Platform Data Engineer at Consultancy.uk, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Google Cloud Platform Data Engineer in England
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 Consultancy.uk, 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 Consultancy.uk. 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 Consultancy.uk
✨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 Consultancy.uk!
✨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.