Data Engineer
1 week ago
Design, develop, and maintain scalable data pipelines to ingest, process, and store structured and unstructured data from multiple sources.
Develop ETL/ELT processes to transform raw data into clean, analysable formats for reporting, analytics and dashboards.
Work with cloud data platforms
Ensure data security and compliance
Integrate and consolidate data from multiple sources, including SSE platforms, enterprise systems, and external APIs.
Optimise data pipelines for performance, reliability, and scalability.
Collaborate with other teams to ensure timely and accurate data delivery.
Perform data validation and quality checks, identifying anomalies, gaps or inconsistencies and resolving them proactively.
Automate data ingestion, transformation, and integration.
Support analytics, machine learning, and business initiatives where necessary.
Continuously evaluate and recommend improvements in data architecture, cloud integrations, and security practices.
Troubleshooting and resolving data-related issues across the environments, ensuring minimal downtime or disruption.
Own the development, maintenance, and operational support of a cloud-based AI platform, ensuring scalability, reliability, and performance for AI workloads.
Translate business requirements into data-driven solutions.
DevOps
Qualification in Computer Science, Information Technology, Data/Software Engineering, Data Science or equivalent.
Cloud Computing or Analytics is a plus.
Data Science / Machine Learning
Data Engineering
MLOps
Python
CI/CD
IaC
Terraform
APIs
Any additional responsibilities assigned in the Agile Working Model (AWM) Charter
Knowledge of cloud data platforms
Experience with big data frameworks
Competency in streaming technologies
Understanding data warehousing and Lake house concepts
Experience with Infrastructure-as-code and DevOps practices
Understanding of data security, governance, and compliance.
Experience in implementing and monitoring solutions
Between 3 - 5 Years
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