Senior Data Engineer

Paradigm Talent
London
2 weeks ago
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Senior Data Engineer

London (Hybrid)

AI Technology

Salary: £80,000-£110,000


Paradigm Talent is currently working with an AI-driven technology company focused on building next-generation automation and intelligence systems for complex, high-stakes environments specifically within the HealthTech space.


The team applies advanced machine learning, computer vision, and multimodal AI to solve critical challenges in operational efficiency and decision-making. They work at the cutting edge of deep learning, object recognition, and large-scale AI systems, delivering solutions that drive real-world impact. If you're passionate about research-driven AI innovation and enjoy working on highly technical challenges, this role is for you.


The Role: Data Engineer (Scalable Data & AI Infrastructure)


We’re looking for a Data Engineer with experience in scalable data pipelines, cloud infrastructure, and real-time data processing. You will be responsible for designing, optimising, and maintaining secure, high-performance data architectures that support machine learning, analytics, and automation-driven applications.


This role offers the opportunity to work in a fast-paced, data-rich environment, collaborating closely with ML engineers, software developers, and product teams to ensure data reliability, security, and efficiency at scale.


What You’ll Do


Data Pipeline Development & Optimization

  • Design, construct, and maintain large-scale data processing and ETL pipelines for structured and unstructured data.
  • Optimize data flow, transformation, and storage, ensuring high efficiency and scalability.
  • Develop and maintain data dashboards for real-time insights and analytics.


Cloud & Infrastructure Engineering

  • Work with SQL/NoSQL databases and cloud data services (AWS) to manage and process large datasets.
  • Optimize data warehousing, modeling, and indexing for performance and scalability.
  • Leverage Apache Spark, Airflow, Kafka, or similar technologies to manage and automate workflows.


Data Security & Quality Control

  • Ensure data security, compliance, and integrity, implementing best practices for access control and governance.
  • Identify and resolve data quality issues proactively, ensuring clean, accurate, and usable data.
  • Collaborate with machine learning and application engineering teams to prepare data for AI-driven applications.


Collaboration & Stakeholder Engagement

  • Work closely with cross-functional teams, including ML researchers, software engineers, and business analysts, to understand data needs and optimize solutions.
  • Support data collection and integration efforts, working with teams across multiple locations to ensure consistency.
  • Bring an analytical mindset, ensuring that data-driven insights align with business and technical goals.


Skills & Experience

  • 3+ years of experience in data engineering or a related field.
  • Strong expertise in ETL development, building and maintaining scalable data pipelines.
  • Proficiency in Python for data processing and automation.
  • Hands-on experience with SQL/NoSQL databases and cloud data platforms (AWS)
  • Understanding of data modelling, data warehousing, and database optimisation.
  • Experience with distributed data processing tools (Apache Spark, Airflow, Kafka, or similar).
  • Proactive approach to identifying and solving data quality issues.
  • Strong project management skills, coordinating with cross-functional teams and data capture staff.

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