At a Glance
- Tasks: Support data-driven projects and help design innovative data solutions.
- Company: Join a rapidly expanding, values-driven team at Daintta.
- Benefits: Enjoy 25 days leave, health insurance, and professional development opportunities.
- Other info: Hybrid working model with exciting social events and perks.
- Why this job: Launch your consulting career while making a real impact on data solutions.
- Qualifications: Degree educated with strong communication and collaboration skills.
The predicted salary is between 25650 - 31350 £ per year.
Daintta are a rapidly expanding, values-driven team of specialists who collaborate with both public and private sector clients across the domains of Cyber, Telecommunications, and Data.
We are seeking a talented and motivated Data graduates to join our team and contribute to our mission of safeguarding the UK through data-driven insights and solutions.
Being a part of our Advanced Professions Programme means you’ll be at the heart of our consulting projects - supporting senior consultants, engaging with clients, and helping to deliver solutions to their most complex challenges.
This is an exciting opportunity to launch your career in consulting, gain exposure to different industries, and develop your skillset in a fast-paced, collaborative and supportive environment.
As a Data Engineering Analyst at Daintta, you will help shape data-driven solutions by supporting the design, testing, and delivery of data pipelines and architectures.
You’ll gain practical experience working with structured and unstructured data, applying ethical data handling principles, and exploring cloud-based technologies—all while building a strong foundation in modern data engineering practices.
Key Responsibilities
- Support the assessment of client data needs by assisting with stakeholder communications, documentation, and technical discovery activities.
- Learn and apply foundational concepts in data extraction, transformation, and loading (ETL/ELT) across structured and unstructured sources.
- Contribute to the development and testing of data engineering solutions across cloud, on-premise, and hybrid environments under the guidance of senior team members.
- Assist in modelling and structuring data for use in analytics, reporting, and business intelligence, while gaining exposure to machine learning and compliance use cases.
- Help ingest, clean, and consolidate data from various formats and standards, ensuring consistency and usability.
- Participate in data migration and conversion tasks, supporting the transition between systems and platforms.
- Develop awareness of ethical data handling practices and relevant data protection legislation.
- Support the implementation of scalable, secure, and reliable data solutions by contributing to design discussions and documentation.
- Deliver high-quality work to agreed timelines, demonstrating initiative and a willingness to learn.
- Assist in preparing materials for client engagements, including reports, presentations, and demos.
- Contribute to internal initiatives that support the growth of the data engineering practice.
- Uphold and promote our values of being transparent, fair, and daring, both internally and externally.
Skills/Knowledge
- Required Skills/Knowledge
- Degree Educated or equivalent.
- Communication: Clear verbal and written communication, especially when translating technical concepts for non-technical audiences.
- Collaboration: Ability to work effectively in multidisciplinary teams and contribute to shared goals.
- Problem-Solving: Analytical thinking and a structured approach to breaking down complex challenges.
- Adaptability: Willingness to learn new tools, frameworks, and methodologies quickly.
- Initiative: Proactive attitude, with the confidence to ask questions and take ownership of tasks.
- Time Management: Ability to manage multiple tasks and meet deadlines in fast-paced environments.
- Attention to Detail: Careful and thorough approach to analysis, documentation, and delivery.
- Client Focus: Professionalism and empathy when engaging with stakeholders and understanding their needs.
- Nice to Have Experience / Knowledge
- ETL/ELT concepts
- SQL and data querying
- Data modelling basics
- Familiarity with cloud platforms (e. g. AWS, Microsoft Azure)
- Data ethics and governance awareness
Location?
Hybrid, with 2-3 days working from Daintta office (London or Cheltenham) or on client site as required.
Benefits
We believe in supporting our people both professionally and personally. Here’s what you can expect when you join us:
Time Off
- 25 days annual leave, plus bank holidays
- Up to 5 days annual training leave with a dedicated training budget
- Up to 3 days annual volunteering leave - give back to the community
- Competitive maternity, paternity, shared parental leave & compassionate leave
Health & Wellness
- Comprehensive Private Health Insurance
- Employee Assistance Programme - 24/7 support services
- £2,000 Flex Cash Allowance, paid pro-rata over the year
Financial Benefits
- 5% pension contribution
- Discretionary company awards and bonuses, based on performance and company targets
- Professional Development
- Up to £1,000 annual training budget (access to additional training and development budget via business case)
- Up to 5 days annual training leave
- 1 professional membership paid annually
- Up to £200 of additional IT budget for new joiners
Perks
- Free breakfast every Tuesday in the London office
- Fortnightly drinks – in London
- Regular social events, quizzes, and guest workshops
- Huckletree perks – including gym and restaurant discounts
- Employee referral programme
- Monthly breakfast club in our Cheltenham office
- Security Information
Due to clients’ requirements, all applications are strictly subject to security clearance requirements relevant to the role.
Data Engineer Analyst employer: Daintta Ltd
Daintta is an exceptional employer that fosters a dynamic and inclusive work culture, where your contributions are valued and respected. With a strong commitment to professional development, employees benefit from generous training budgets, flexible working arrangements, and a supportive environment that encourages innovation and creativity. Located in vibrant London or Cheltenham, you will have the opportunity to engage with cutting-edge defence projects while enjoying a range of perks and benefits that promote both personal and professional growth.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer Analyst
✨Get Involved in Data Science Meetups
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✨Show Off Your Projects
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✨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 Daintta Ltd.
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We think you need these skills to ace Data Engineer Analyst
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!
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Craft a Tailored Cover Letter:For a full-time role at Daintta Ltd, 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 Daintta Ltd. 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 Daintta Ltd
✨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 Daintta Ltd!
✨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.
