At a Glance
- Tasks: Design and implement data architectures for digital transformation across various industries.
- Company: Join a leading consultancy focused on sustainable data solutions.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Mentorship opportunities available to support your career development.
- Why this job: Make a real impact by solving complex data challenges for diverse clients.
- Qualifications: Strong data engineering skills and experience with cloud technologies required.
The predicted salary is between 80000 - 100000 £ per year.
Our Data, AI, Solutions & Engineering (DAISE) practice is looking for an experienced Data Engineer to join the team.
In DAISE, we are focused on delivering value‑adding, sustainable data capabilities that are aligned to our client’s specific needs.
This expertise is applied across clients in all of our industry market sectors (Financial Services, Products & Services, Energy & Resources, Pharmaceutical & Lifesciences and Government).
- What You Will Be Doing
- Defining and implementing on‑premise or cloud architectures (e. g., a cloud data warehouse, data lake or data platform) to enable digital transformation.
- Working with clients on data warehousing, building operational ETL/ELT data pipelines across a number of sources, and constructing relational and dimensional data models.
- Performing maturity assessments across clients’ data capabilities and recommending improvements.
- Building technology blueprints and advising clients on the different technology options.
- Translating business requirements (both functional and non‑functional) into solutions, ensuring compliance with the organisation's strategy, policies and standards and, in some cases, helping customers to define new policies, principles and standards.
- Helping clients to identify risks and mitigations for their complex data programmes, and supporting a transition to modern cloud‑based infrastructures (AWS, Azure, GCP) by leveraging related architecture patterns (e. g., APIs, events).
- Working independently with clients in key areas of data governance, such as defining principles including, but not limited to, master data management, data lineage and data security.
- Experience with mentoring, guiding, training and/or upskilling people on technical concepts who are earlier in their career within the team, and supporting their growth.
- Your Skills And Experience
- Passionate individual who is excited by problems with data and can bring a good mix of technical delivery and core consulting skills in client engagements.
- Ability to own and run complex client engagements, interact with leaders across industry, work with senior stakeholders to help them understand and frame their problems, assess their current state, and make impactful recommendations that shape their thinking.
- Strong hands‑on expertise in data engineering, delivering data architectures, data pipelines and solutions that are robust and scalable using modern delivery frameworks and tools (e. g., Databricks).
- Experience in using cloud technologies (Azure, AWS, GCP) as both infrastructure and as a service, as well as big data platforms on‑premise or cloud setup.
- Knowledge of different technology stacks including common legacy and modern stacks, experience applying Dev Ops practices to data engineering, and ability to build CI/CD pipelines.
- Competent in SQL and at least one modern programming language, such as Python.
- Understanding of key core concepts like distributed computing, batch & stream processing, functional and object‑oriented programming, how pipelines are built and deployed on cloud, pipeline schedules and SLAs.
- Well‑versed with documentation and artefacts that need to accompany the solution design and delivery work.
- #J-18808-Ljbffr
Senior Consultant, Data Engineer in London employer: hackajob
At hackajob, we pride ourselves on being an exceptional employer that fosters a culture of innovation and inclusivity. Our diverse team thrives in a high-performance environment where your contributions directly impact our multi-asset platform's success. With ample opportunities for professional growth and a commitment to employee development, joining us means being part of a forward-thinking company that values your expertise and ambition.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Consultant, Data Engineer in London
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We think you need these skills to ace Senior Consultant, Data Engineer in London
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 hackajob, 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 hackajob. 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 hackajob
✨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 hackajob!
✨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.
