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

Apply Now

Data Engineer

Aspia Space
Penryn
2 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Direct message the job poster from Aspia Space

Aspia Space is building the next generation of planetary intelligence. We transform observational data into trusted, consumable intelligence for agriculture, finance, environmental planning and policy.

From our offices in Harwell and Cornwall, we push Earth data to its limits to deliver insights no one else can, developing products that combine satellite imagery and expert ground truth with the very best observational science and deep learning tools to support clients across the world, powering everything from smallholder farming programmes in Africa to biodiversity net gain compliance in the UK.

We’re a multidisciplinary team of scientists, engineers, and product strategists who believe in delivering practical impact. Our ambition is global, but our focus is always local, measurable, and relevant.

Role Overview:

We’re looking for a highly skilled Data Engineer / Data Architect who can hit the ground running and join us in our Penryn office. You will be instrumental in building, managing, and optimising our data infrastructure across both on-premise HPCs and cloud platforms. You’ll work closely with ML engineers and researchers to wrangle, clean, and prepare large datasets—including geospatial data—for training our large-scale AI models.

Key Responsibilities:

•Architect, design, and manage scalable data pipelines and infrastructure across on-premise and cloud environments (AWS S3, Redshift, Glue, Step Functions).

•Ingest, clean, wrangle, and preprocess large, diverse, and often messy datasets—including structured, unstructured, and geospatial data.

•Collaborate with ML and research teams to ensure data pipelines align with model training requirements and schedules.

•Develop and maintain robust metadata management and data versioning strategies.

•Optimise data workflows for performance, reproducibility, and cost efficiency.

•Implement automated processes for data quality checks, validation, and governance.

•Champion data security, compliance, and privacy best practices.

•Monitor and troubleshoot data issues in real-time, ensuring high availability and integrity.

•3+ years of experience in data engineering, data architecture, or similar roles.

•Expert proficiency in Python, including popular data libraries (Pandas, PySpark, NumPy, etc.).

•Strong experience with AWS services—specifically S3, Redshift, Glue (Athena a plus).

•Solid understanding of applied statistics.

•Hands-on experience with large-scale datasets and distributed systems.

•Experience working across hybrid environments: on-premise HPCs and cloud platforms.

•Proficiency with Linux, bash scripting, and git.

•Proven ability to write clean, maintainable, and testable code.

•Ability to thrive in a fast-paced, dynamic environment with shifting priorities.

•Excellent problem-solving and communication skills.

Proximity to our Penryn office in Cornwall, UK.

•Experience supporting machine learning workflows, especially for large model training.

•Familiarity with handling geospatial datasets and related libraries (e.g., GDAL, GeoPandas, Rasterio).

•Familiarity with data cataloguing tools and practices.

•Prior experience in a startup or high-growth tech company.

•Familiarity with containerisation (Docker), orchestration tools (Airflow, Prefect), and CI/CD workflows.

•Understanding of foundational MLOps and data-centric AI practices.

•Experience of working in an Agile environment.

What We Offer:

•The opportunity to shape the data backbone of a transformative AI company.

•A dynamic and collaborative work environment where initiative is valued.

•Competitive salary and company benefits including private health insurance.

•Hybrid work options

•Access to cutting-edge compute infrastructure and tools.

How To Apply:

To apply, please send a PDF of your CV (and an optional cover letter) to Laura Botha at .

Applications will be reviewed on a rolling basis until the position is filled.

Please also indicate that you are aware this role requires you to be on-site in the Cornish office 3-4 days a week.

Seniority level

  • Seniority levelMid-Senior level

Employment type

  • Employment typeFull-time

Job function

  • Job functionInformation Technology
  • IndustriesDefense and Space Manufacturing

Referrals increase your chances of interviewing at Aspia Space by 2x

Sign in to set job alerts for “Data Engineer” roles.

Newquay, England, United Kingdom 2 days ago

Helston, England, United Kingdom 3 weeks ago

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.


#J-18808-Ljbffr

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.

The Future of Machine Learning Jobs: Careers That Don’t Exist Yet

Machine learning (ML) has become one of the most powerful forces reshaping the modern world. From voice assistants and recommendation engines to fraud detection and medical imaging, it underpins countless applications. ML is no longer confined to research labs—it powers business models, public services, and consumer technologies across the globe. In the UK, demand for machine learning professionals has risen dramatically. Organisations in finance, retail, healthcare, and defence are embedding ML into their operations. Start-ups in Cambridge, London, and Edinburgh are pioneering innovations, while government-backed initiatives aim to position the UK as a global AI leader. Salaries for ML engineers and researchers are among the highest in the tech sector. Yet despite its current importance, machine learning is only at the beginning of its journey. Advances in generative AI, quantum computing, robotics, and ethical governance will reshape the profession. Many of the most vital machine learning jobs of the next two decades don’t exist today. This article explores why new careers will emerge, the roles likely to appear, how today’s roles will evolve, why the UK is well positioned, and how professionals can prepare now.

Seasonal Hiring Peaks for Machine Learning Jobs: The Best Months to Apply & Why

The UK's machine learning sector has evolved into one of Europe's most intellectually stimulating and financially rewarding technology markets, with roles spanning from junior ML engineers to principal machine learning scientists and heads of artificial intelligence research. With machine learning positions commanding salaries from £32,000 for graduate ML engineers to £160,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this pioneering and rapidly evolving field. Unlike traditional software engineering roles, machine learning hiring follows distinct patterns influenced by AI research cycles, model development timelines, and algorithmic innovation schedules. The sector's unique combination of mathematical rigour, computational complexity, and real-world application requirements creates predictable hiring windows that strategic professionals can leverage to advance their careers in developing tomorrow's intelligent systems. This comprehensive guide explores the optimal timing for machine learning job applications in the UK, examining how enterprise AI strategies, academic research cycles, and deep learning initiatives influence recruitment patterns, and why strategic timing can determine whether you join a groundbreaking AI research team or miss the opportunity to develop the next generation of machine learning algorithms.

Pre-Employment Checks for Machine Learning Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in machine learning reflects the discipline's unique position at the intersection of artificial intelligence research, algorithmic decision-making, and transformative business automation. Machine learning professionals often have privileged access to proprietary datasets, cutting-edge algorithms, and strategic AI systems that form the foundation of organizational competitive advantage and automated decision-making capabilities. The machine learning industry operates within complex regulatory frameworks spanning AI governance directives, algorithmic accountability requirements, and emerging ML ethics regulations. Machine learning specialists must demonstrate not only technical competence in model development and deployment but also deep understanding of algorithmic fairness, AI safety principles, and the societal implications of automated decision-making at scale. Modern machine learning roles frequently involve developing systems that impact hiring decisions, financial services, healthcare diagnostics, and autonomous operations across multiple regulatory jurisdictions and ethical frameworks simultaneously. The combination of algorithmic influence, predictive capabilities, and automated decision-making authority makes thorough candidate verification essential for maintaining compliance, fairness, and public trust in AI-powered systems.