Senior AWS Data Engineer — Build Governed Data Products

Microlise; Newthorpe; On-site; GBP 20,000 - 60,000; Full time

Benefits offered by this job

EV car salary sacrifice

Private medical insurance

25 days holiday + bank holidays

Costco membership

Wellbeing support

Annual staff awards

Job summary

Microlise is seeking a data engineering professional to design, build, and maintain data pipelines and governance-aware data products. You will translate complex business needs into robust data models and collaborate with AI teams to enable analytics across the organisation.

The role emphasizes end-to-end data product lifecycle ownership, data quality, and stakeholder alignment to meet performance and SLA expectations.

Qualifications

• Experience in data engineering and building data pipelines.
• Knowledge of data modelling, governance and quality frameworks.
• Experience with analytics or AI-ready datasets.
• Ability to translate business requirements into data solutions.

Responsibilities

• Design, build, and maintain data pipelines and transformations.
• Create reusable, governed data products for analytics and AI teams.
• Translate business needs into structured, reliable datasets and data models.
• Own the end-to-end lifecycle of data products from creation through to optimisation.
• Apply and monitor data quality, validation, and governance standards.
• Manage metadata, lineage, data contracts, and compliance requirements.
• Work closely with stakeholders to understand data usage, dependencies, and impact.
• Ensure data products meet quality, performance, and SLA expectations.

Skills

Data engineering

Data pipelines

AI-ready data

Requirements translation

Stakeholder management

Tools

AWS

Cloud

Mobile

Job description

Microlise is seeking a data engineering professional to design, build, and maintain data pipelines and governance-aware data products. You will translate complex business needs into robust data models and collaborate with AI teams to enable analytics across the organisation.

The role emphasizes end-to-end data product lifecycle ownership, data quality, and stakeholder alignment to meet performance and SLA expectations.