Senior Data Engineer

The Senior Data Engineer designs, implements and oversees maintenance of data flow channels and data processing systems that support the collection, storage, batch and real-time processing, and analysis of information from structured and unstructured sources in a scalable, repeatable and secure manner. He/She assists data scientists with the extraction of valuable insights from data sets to derive valuable and actionable insights and recommendations that support business requirements. He involves in rollouts, upgrades, implementation and release of data system changes as required for streamlining of internal practices. He is proficient in database systems, scripting and programming languages required by the organization. He is also familiar with the relevant software platforms on which the solution is deployed on. The Senior Data Engineer possesses natural inclination for understanding business processes and relevant data requirements. He easily builds rapport with others and is able to put forth his ideas and recommendations in a persuasive manner, to influence stakeholders and decisions.

Skills and Competencies

Technical Skills & Competencies

Business Needs Analysis
Proficiency Level
"Elicit and analyze business requirements from key stakeholders and assess relevant solutions and their potential impact"
3
Change Management
Proficiency Level
"Recommend business activities required to integrate and roll out new changes and drive the execution of change control procedures, engaging stakeholders in the process "
4
Computational Modelling
Proficiency Level
"Develop and utilize new algorithms and advanced statistical models to enable the production of desired outcomes "
4
Configuration Tracking
Proficiency Level
"Develop and update a configuration management plan, determining systems and techniques to track changes and revisions "
3
Data Design
Proficiency Level
"Design data models and data flow diagrams and mechanisms to optimize the flow, maintenance, storage and retrieval of data "
4

Generic Skills & Competencies

Leadership
Proficiency Level
Lead by example at organisational level. Inspire, motivate and guide others to adopt a point of view, make changes or take action. Cultivate an open, cooperative and collaborative learning culture for the organization.
Advanced
Developing People
Proficiency Level
Provide coaching to others to develop their skills and knowledge on their jobs to enhance performance.
Intermediate
Communication
Proficiency Level
"Articulate and discuss ideas and persuade others to achieve common outcomes "
Intermediate
Transdisciplinary Thinking
Proficiency Level
Synthesize knowledge and insights across disciplinary boundaries to aid strategic decisions and foster cooperation within and outside of the organization.
Advanced
Computational Thinking
Proficiency Level
Develop and create computational models, tools and techniques to implement new solutions and apply to other problems.
Advanced

Critical Work Functions and Key Tasks

Identify business needs

• Assess the suitability of data structure to ensure availability, integrity, 
quality, scalability and accessibility of data 
• Translate the business' data needs into technical system requirements 
• Evaluate suitability of technologies and products in database and 
data processing for integration and storage

Build and maintain data pipeline

• Build data flow channels and processing systems to extract, 
transform, load and integrate data 
• Validate data extraction, preparation and processing systems 
for accuracy of data and outputs 
• Create data storage plans and solutions for information storage 
and extraction 
• Lead project rollouts, upgrades, implementation and release of 
data system changes 
• Analyse data system performance and develop solutions for improvements 
• Build a metadata system to ensure documentation and cataloguing 
of all available data 
• Formulate data backup and fail-safe plans as part of business 
continuity planning 
• Ensure the security, privacy and anonymity of users accessing data systems

Optimise performance of solutions

• Evaluate existing technologies and technology practices 
• Resolve data integrity, performance, and availability issues 
• Identify opportunities for improvements and optimisation
to systems and processes 
• Automate processes focusing on repeatability and reliability

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