~22m ago

Data Engineer Analyst

United Kingdom·London

Data EngineerData

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Quick Summary

Key Responsibilities

Clear verbal and written communication, especially when translating technical concepts for non-technical audiences.

Technical Tools

Data EngineerData

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.

Responsibilities

~1 min read

→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.

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.