At a Glance
- Tasks: Design and build data pipelines, work with SQL and Python, and document technical processes.
- Company: Join a leading consulting platform connecting experts with exciting remote projects.
- Benefits: Earn $130–$190/hour, fully remote work, and flexible hours.
- Other info: Engage in a dynamic project with potential for extension based on performance.
- Why this job: Make an impact in data engineering while working on innovative projects from anywhere in the UK.
- Qualifications: Hands-on experience in data engineering, strong SQL and Python skills required.
The predicted salary is between 190 - 190 £ per hour.
We are sharing a specialised full-time consulting opportunity for UK-based Data Engineers with hands-on experience building and operating production data pipelines, platforms, and modern analytics infrastructure. This short, intensive project focuses on producing professional data-engineering deliverables based on the kinds of systems, documentation, and technical decisions encountered in day-to-day production work. Selected experts will contribute practical judgement across data pipelines, orchestration, streaming, warehousing, and cloud data platforms.
Key Responsibilities
- Data Pipeline Engineering
- Design and document production-grade data pipelines
- Work across ETL and ELT workflows
- Assess data movement, transformation, and processing requirements
- Apply practical engineering judgement to realistic data-platform scenarios
- Produce clear technical deliverables reflecting professional data-engineering practice
- SQL & Python Development
- Apply strong SQL and Python skills to data engineering workflows
- Develop or review transformations, processing logic, and supporting technical materials
- Evaluate data-processing approaches for correctness and scalability
- Structure technical work clearly for downstream review
- Apply production experience rather than purely theoretical knowledge
- Workflow Orchestration
- Work with orchestration concepts and platforms such as Airflow
- Design or assess dependency management and scheduled data workflows
- Review pipeline sequencing and operational considerations
- Identify issues affecting reliability or maintainability
- Document orchestration decisions clearly
- Streaming & Distributed Processing
- Apply experience with streaming and large-scale data processing
- Work with technologies such as Kafka and Spark
- Evaluate architecture and implementation choices for distributed workloads
- Assess reliability, scalability, and data-flow considerations
- Apply practical judgement from production environments
- Data Warehousing & Analytics Engineering
- Work with modern data warehouse and analytics architectures
- Apply experience with platforms such as Snowflake, BigQuery, or Databricks
- Develop or review transformation workflows using tools such as dbt
- Assess data modelling and warehouse design decisions
- Produce structured deliverables reflecting real-world analytics engineering practice
- Cloud Data Platforms
- Apply experience working with data systems on AWS, GCP, or Azure
- Review cloud architecture and platform decisions
- Assess data-storage, processing, and integration approaches
- Evaluate technical trade-offs across cloud-based data environments
- Document implementation and architecture decisions clearly
- Technical Documentation
- Produce professional documents and deliverables based on real data-engineering work
- Explain architectural and implementation decisions clearly
- Structure technical information so that workflows and assumptions can be reviewed consistently
- Document production practices, constraints, and engineering considerations
- Contribute to projects where documentation and structured technical reasoning are central to the work
Ideal Profile
- Hands-on professional experience as a Data Engineer, Senior Data Engineer, Staff Data Engineer, Analytics Engineer, Data Platform Engineer, Data Architect, or closely related professional
- Strong production experience building and owning data pipelines
- Strong proficiency in SQL and Python
- Practical experience across ETL/ELT, orchestration, streaming, and data warehousing
- Experience with relevant technologies such as:
- Spark
- Kafka
- Airflow
- dbt
- Snowflake
- BigQuery
- Databricks
- Experience working with AWS, GCP, or Azure
- Comfortable producing both hands-on technical work and structured professional documentation
- Able to work independently while collaborating with specialists from adjacent technical domains
- Must be based in the United Kingdom
- Must have the right to work in the United Kingdom
Engagement Details
- Full-time independent contractor engagement
- Fully remote within the United Kingdom
- Compensation: $130–$190/hour
- Expected commitment: 40 hours per week
- Project period: 14 September to 10 October 2026
- Collaboration follows UK business hours
- Candidates should not be committed to other projects requiring significant hours during this engagement
- Smaller side projects may be compatible with the engagement
- Selection includes a resume and work-history review plus a short domain-expertise assessment
- Projects may be extended, shortened, or concluded based on project needs and performance
- Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party
- H1-B and STEM OPT support is unavailable for this engagement
About the Platform
This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.
Remote | Data Engineer (UK-Based) — $130–$190/hour in London employer: 24-Mag
At 24-MAG LLC, we pride ourselves on being an exceptional employer that values the expertise of UK-based architects. Our remote consulting opportunities offer flexible scheduling and competitive compensation, allowing professionals to apply their architectural judgment in a focused environment while contributing to meaningful projects. With a strong emphasis on professional growth and a supportive work culture, we empower our consultants to excel in their roles and make impactful contributions to the architectural community.
StudySmarter Expert Advice🤫
We think this is how you could land Remote | Data Engineer (UK-Based) — $130–$190/hour in London
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We think you need these skills to ace Remote | Data Engineer (UK-Based) — $130–$190/hour 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!
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How to prepare for a job interview at 24-Mag
✨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!
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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 24-Mag!
✨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.
