Senior Data Engineer: AI, ML Pipelines & Data Innovation

Mncinsider; Milton Keynes; On-site; GBP 85,000 - 120,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Retirement plan

Job summary

Unisys in Milton Keynes is seeking a Senior Data Engineer to design and implement data pipelines, develop ML models, and translate business needs into technical solutions. You will work with stakeholders to understand requirements and leverage AI/LM technologies to deliver actionable insights.

The role involves collaborating with data scientists and engineers, and communicating findings to varied audiences while staying aligned with enterprise data governance and quality practices.

Qualifications

• Proven experience in data engineering and data science roles.
• Strong understanding of machine learning algorithms and statistical modeling techniques.
• Experience with large and complex datasets.
• Proficiency in programming languages such as Python, R, or Java.
• Experience with data visualization tools such as Tableau or Power BI.
• Familiarity with cloud computing platforms such as AWS, Azure, or Google Cloud.

Responsibilities

• Design and implement data pipelines for processing large datasets.
• Develop and run machine learning models to solve business problems.
• Communicate findings and recommendations to diverse audiences.
• Collaborate with data scientists and engineers to create innovative solutions.
• Participate in code reviews and improve data science capabilities.

Skills

algorithm design

analytical thinking

data engineering

machine learning

programming skills

Tools

Python

R

Java

AWS

Azure

Google Cloud

Job description

Unisys in Milton Keynes is seeking a Senior Data Engineer to design and implement data pipelines, develop ML models, and translate business needs into technical solutions. You will work with stakeholders to understand requirements and leverage AI/LM technologies to deliver actionable insights.

The role involves collaborating with data scientists and engineers, and communicating findings to varied audiences while staying aligned with enterprise data governance and quality practices.