Data Engineer

Understand data science challenges and design, build and schedule end-to-end data pipelines.
Select appropriate big data technologies to solve technical and business problems efficiently.
Automate data science pipelines, deploy machine learning algorithms and monitor their performance.
Build Customer 360 solutions and feature stores for a range of machine learning use cases.
Develop data models for machine learning feature stores using high-velocity databases with flexible schemas.
Identify data sources across the organisation and integrate them into a big data lake.
Translate business challenges into end-to-end analytics use cases, data structures and data model requirements.
Collaborate with business stakeholders to agree scope, deliverables, processes and expected outcomes.
Provide technical guidance to senior technologists and business leaders on data architecture, data models and metadata management.
Partner with database teams to address data quality, accuracy, integrity and usability requirements.
Create and modify programs that extract information from organisational databases.
Work with large datasets and distributed computing, simulation and optimisation tools.
Diagnose and resolve issues affecting big data platforms and frameworks.
Communicate technical concepts and recommendations clearly to business and project stakeholders.