Playing a leadership role in an agile delivery team
Leading aspects of the data and analytics lifecycle
Responsible for identifying appropriate technologies and architecting data platforms
Guiding architectural and technical decisions across data engineering solutions
Supporting teams in designing data platforms for AI and machine learning

Engineering Big Data patterns and solving complex data challenges
Designing and architecting scalable data platforms including data lakes and ingestion pipelines
Engineering and modelling best practices for both RDMS and NoSQL databases
Designing distributed data processing solutions using technologies such as Apache Spark (particularly DataBricks), Google BigQuery or similar platforms
Designing solutions using the most appropriate cloud-based services (AWS, Azure, GCP etc.) and cloud-native data patterns
Implementing large-scale data ingestion pipelines including batch, micro-batch and streaming processing approaches
Designing data platforms that support advanced analytics, machine learning and AI-driven solutions
Confidently taking on challenges and being responsible for outcomes
Creating a collaborative team environment where everyone’s opinion is heard, but you know when to be assertive, back down or escalate
Great communication skills, in particular: presenting, collaborating and partnering with stakeholders
Understanding the way projects affect your client’s success and adds value to their business

Lead Consultant, Data & AI Engineering

Key skills