Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Engineer

SRG Network
London
1 year ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer | Blockchain | London | Hybrid

Data Engineer with a keen focus on blockchain and distributed ledger technology required for a not-for-profit organisation focused on developing the blockchain ecosystem.

The Data Engineer will be pivotal in managing, curating, optimising, and securing datasets specifically related to cryptocurrency discussions across various platforms. The ideal candidate will be adept in web scraping, data quality assurance using AI, data integration, ensuring data security and compliance, and maintaining detailed documentation.

What’s on offer to you?

Work with leading academics Work with leading blockchain technology Be part of an exciting new project with AI

What You Will Be Doing

Data Collection: Identify relevant chat sources, groups, and forums on platforms discussing particular topics. Maintain and develop web scraping tools or APIs for periodic data extraction. Data Quality Assurance: Develop and implement AI-based procedures for quality control of data and data sources to eliminate inaccuracies and anomalies. Create tools for monitoring data sources for changes and updates, adapting data collection and cleaning processes accordingly. Data Integration: Collaborate with data scientists and analysts to integrate collected data into various projects and analysis tools. Ensure smooth data flow and integration with other data sources within the organisation. Data Security and Compliance: Uphold the security and privacy of collected data in compliance with relevant regulations and company policies. Documentation: Maintain clear and comprehensive documentation of data sources, collection methods, and workflows. Produce reports and documentation for both internal and external stakeholders as required. Monitoring and Reporting: Develop and maintain systems to monitor the performance and health of data collection processes.

What You Will Need to Succeed in This Role

Bachelor’s degree in Computer Science, Data Science, or a related field. Knowledge of Data Structures and Databases is a must. Demonstrable experience in data engineering or a similar role, with a focus on web scraping and data collection. Proficient in programming languages such as Python, SQL. Knowledge in TypeScript is a must. Familiarity with blockchain technology. Knowledge of data privacy laws and compliance requirements. Strong analytical and problem-solving skills. Excellent communication and collaboration abilities. Preferred: Advanced degree in a relevant field. Preferred: Experience with big data technologies and cloud services. Preferred: Proficiency in AI and machine learning techniques for data quality assurance.

Keywords: Data Engineer | AI | Blockchain | SQL | Typescript

Job Information

Job Reference: Salary: Salary From: £0Salary To: £0Job Industries: ITJob Locations: London, United KingdomJob Types: Permanent

Apply for this Job

Data Engineer

Data Engineer | Blockchain | London | Hybrid

Data Engineer with a keen focus on blockchain and distributed ledger technology required for a not-for-profit organisation focused on developing the blockchain ecosystem.

The Data Engineer will be pivotal in managing, curating, optimising, and securing datasets specifically related to cryptocurrency discussions across various platforms. The ideal candidate will be adept in web scraping, data quality assurance using AI, data integration, ensuring data security and compliance, and maintaining detailed documentation.

What's on offer:

Work with leading academics Work with leading blockchain technology Be part of an exciting new project with AI

What you'll be doing:

Data Collection: Identify relevant chat sources, groups, and forums on platforms discussing particular topics. Maintain and develop web scraping tools or APIs for periodic data extraction. Data Quality Assurance: Develop and implement AI-based procedures for quality control of data and data sources to eliminate inaccuracies and anomalies. Create tools for monitoring data sources for changes and updates, adapting data collection and cleaning processes accordingly. Data Integration: Collaborate with data scientists and analysts to integrate collected data into various projects and analysis tools. Ensure smooth data flow and integration with other data sources within the organisation. Data Security and Compliance: Uphold the security and privacy of collected data in compliance with relevant regulations and company policies. Documentation: Maintain clear and comprehensive documentation of data sources, collection methods, and workflows. Produce reports and documentation for both internal and external stakeholders as required. Monitoring and Reporting: Develop and maintain systems to monitor the performance and health of data collection processes.

Data Engineer | AI | Blockchain | SQL | Typescript

Job summary:

Key requirements:

Bachelor’s degree in Computer Science, Data Science, or a related field. Knowledge of Data Structures and Databases is a must. Demonstrable experience in data engineering or a similar role, with a focus on web scraping and data collection. Proficient in programming languages such as Python, SQL. Knowledge in TypeScript is a must. Familiarity with blockchain technology. Knowledge of data privacy laws and compliance requirements. Strong analytical and problem-solving skills. Excellent communication and collaboration abilities. Preferred: Advanced degree in a relevant field. Preferred: Experience with big data technologies and cloud services. Preferred: Proficiency in AI and machine learning techniques for data quality assurance.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.