Engineer (Data, Platform, Cloud, DevOps, ML, Data Visualisation) X11
Position summary
Introduction
Job description
- Design and implement scalable and robust processes for ingesting and transforming large data sets, developing platforms, and deploying cloud solutions.
- Design, implement and maintain data pipelines that ingest large, complex data sets from a variety of data sources.
- Implement and support cloud strategies aligned with data architecture, security and governance.
- Apply DevOps practices to enhance efficiency and automation for greater scalability, including infrastructure and solutions as code.
- Integrate machine learning models into data processes and ML platform.
- Design and implement scalable and robust processes for visualising large data sets, enabling self-service visualisation and analytics.
- Develop APIs to expose the data to enterprise applications and 3rd party vendors.
- Work with various stakeholders across the organisation to understand data requirements and apply technical knowledge of data management to solve key business problems.
- Provide support in the operational environment with all relevant support teams for data services.
Minimum requirements
JOB REQUIREMENTS
· Education Background: Bachelor’s degree in Computer Science, Business Informatics, Mathematics, Statistics, Engineering, or a related field.
· Profession Experience: 4-5 years of relevant engineering experience.
· Technical Skills:
· Strong understanding of data structures, algorithms, and software design.
· Experience with structured and unstructured data, different data stores, and traditional RDBMS and data warehouses.
· Proficiency in programming languages such as Python, Scala, Java, and C .
· Practical experience with Apache Spark and cloud services (e.g., AWS, Azure, GCP).
· Experience with version control systems like Git and SVN.
· Proficiency in data visualisation tools such as PowerBI, Quicksight and QlikSense.
· Experience with DevOps practices, including CI/CD and Infrastructure as Code.
· Specialised Skills:
· Data Engineering: Experience with big data, ETL, and data management processes.
· Platform Engineering: Experience with cloud platform development and maintenance.
· Cloud Engineering: Experience with cloud architecture and API development.
· DevOps: Experience with DevOps practices, architecture, and operation.
· ML Engineering: Experience with machine learning frameworks and model integration.
· Data Visualisation: Experience with data visualisation tools and techniques.
· Soft Skills:
· Excellent verbal and written communication skills.
· Strong analytical and problem-solving abilities.
· Ability to work well in an agile, collaborative team environment.
· Continuous learning mindset and commitment to professional development.
· Innovative thinking and adaptability to changing business needs.
ADDITIONAL CRITERIA
- Analytical Mindset: Demonstrates a strong analytical and problem-solving ability, capable of breaking down complex data issues and devising effective solutions.
- Collaboration and Communication: Exhibits excellent interpersonal and communication skills, with the ability to articulate complex data concepts to non-technical stakeholders. Must foster a collaborative team environment and efficiently work across different departments.
- Continuous Learning: Has a strong commitment to continuous professional development, staying ahead of the latest trends and technologies in data engineering and analytics. Willingness to pursue relevant certifications and training.
- Innovative Thinking: Displays innovative thinking and a proactive approach to identifying and pursuing opportunities to improve data processes and solutions. Comfortable proposing and experimenting with new technologies or methodologies to enhance data capabilities.
- Adaptability: Demonstrates flexibility in adapting to changing business needs and technology landscapes. Can efficiently manage multiple priorities and adapt strategies in a fast-paced environment.
- Cultural Fit: Aligns with the organisation's culture and values, contributing positively to team dynamics and company morale. Demonstrates integrity, accountability, and a strong work ethic.
