Open roleExternal
AI/ML Data Engineer
- nottingham, nottinghamshire, NG1 6EL, United Kingdom
- Hybrid
- Full time
- £63,000 - £63,000 Per Annum
Job Description
About the Role
Our client is seeking a skilled and detail-oriented AI/ML Data Engineer to join their growing data science team in Nottingham . This hybrid role is essential for building and maintaining the robust data infrastructure that powers our AI and machine learning initiatives. You will be responsible for collecting, cleaning, transforming, and optimizing large datasets to ensure they are readily available and suitable for model training and analysis. This is a key position for someone passionate about data pipelines and enabling advanced analytics and AI development within the company.
Key Responsibilities
- Design, construct, install, test, and maintain highly scalable data management systems.
- Build and optimize ETL/ELT pipelines for various data sources, ensuring data quality and integrity.
- Collaborate with data scientists and ML engineers to understand data requirements for model development.
- Implement data warehousing solutions and optimize database performance.
- Develop and maintain data models and schemas to support AI and analytics needs.
- Ensure data security and compliance with relevant regulations.
Requirements
- Bachelor's degree in Computer Science, Engineering, or a related quantitative field.
- Proven experience as a Data Engineer, with a strong focus on supporting AI/ML projects.
- Proficiency in SQL and experience with relational and NoSQL databases.
- Experience with data pipeline orchestration tools (e.g., Airflow) and big data technologies (e.g., Spark, Hadoop).
- Familiarity with cloud data platforms (e.g., AWS Redshift, Azure Data Lake, Google BigQuery).
- Strong understanding of data modeling, data warehousing concepts, and ETL/ELT processes.
Benefits
- Competitive salary and comprehensive benefits package.
- Hybrid working model providing work-life balance.
- Opportunities for professional development and training in data technologies.
- Engaging work contributing to the company's data-driven strategy.
- A supportive and collaborative team environment.