Listing reference: woolw_000888
Listing status: Online
Apply by: 13 August 2024
Position summary Industry: Wholesale & Retail Trade
Job category: FMCG, Retail, Wholesale and Supply Chain
Location: Western Cape
Contract: Permanent
Remuneration: Market Related
EE position: No
Introduction An Engineer responsible for designing and implementing scalable and robust processes to support various engineering capabilities. This role includes extracting, transforming, and consolidating data, developing and maintaining a data platform, implementing cloud solutions, supporting DevOps practices, applying machine learning techniques, and creating data visualisations.
Key Responsibilities 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. Job Requirements Education Background: Bachelor's degree in Computer Science, Business Informatics, Mathematics, Statistics, Engineering, or a related field.
Professional 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. Experience with big data, ETL, and data management processes. Experience with cloud platform development and maintenance. Experience with cloud architecture and API development. Experience with DevOps practices, architecture, and operation. Experience with machine learning frameworks and model integration. Experience with data visualisation tools and techniques. 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.
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