Lead Data Engineer - AI/Platform Architect

Credera; Greater London; On-site; GBP 84,000 - 100,000; Full time

Benefits offered by this job

Competitive salary

Career progression opportunities

Global teams

Job summary

Credera in the United Kingdom is seeking a Lead Engineer to drive data engineering delivery on client projects, balancing internal initiatives and external impact.

You will lead multiple teams, build data pipelines with Spark, Python or SQL, and utilise AWS data services including SageMaker to support analytics and AI workloads. The role requires collaboration across a matrix organisation and a proactive approach to governance and risk.

Qualifications

• Lead multiple complex areas of data engineering delivery to time, cost and quality.
• Manage teams effectively, acting as escalation point for decisions.
• Build data pipelines using Spark, Python or SQL.
• Work with AWS data and AI/ML services like SageMaker.
• Experience with big data platforms on AWS (EMR, Databricks, Snowflake).
• Build data platforms (Lakes, Lakehouses or Data Meshes) for analytics.
• Understand Data Security, Governance and responsible AI principles.
• Partner with senior stakeholders to drive delivery outcomes.
• Anticipate risk and coordinate multi-functional SMEs.
• Drive innovation and upskill engineers; continuously learn.

Responsibilities

• Lead delivery across client projects with minimal direction.
• Upskill and mentor engineers and client counterparts.
• Develop and productionise data and AI/ML solutions.
• Collaborate in a matrix organisation to achieve outcomes.
• Coordinate with stakeholders to ensure alignment and governance.

Skills

Leadership

Data pipelines

Spark/Python/SQL

AWS data services

Stakeholder management

Mentoring

Tools

Spark

Python

SQL

SageMaker

EMR

Databricks

Snowflake

Job description

Credera in the United Kingdom is seeking a Lead Engineer to drive data engineering delivery on client projects, balancing internal initiatives and external impact.

You will lead multiple teams, build data pipelines with Spark, Python or SQL, and utilise AWS data services including SageMaker to support analytics and AI workloads. The role requires collaboration across a matrix organisation and a proactive approach to governance and risk.