Job Description

Requirements

• An appropriate post-graduate qualification (BSc, Engineering, or similar)
• Relevant programming qualifications and / or certifications
• Relevant Agile certification is preferable
• 10 - 12 years' experience in a Data Engineering role building and optimizing data pipelines, architectures and data sets
• Constructing data acquisition, warehousing and reporting solutions
• Advanced working SQL knowledge and 5 years' experience working with relational databases, query authoring (SQL)
• Experience with a variety of databases, technologies, languages and visualisation engines (Power BI, Tableau, SAS).
• 3 - 4 years' experience building analytics tools that utilize the data pipeline to provide actionable insights into customer management, operational efficiency and other key business performance metrics.

• Design and implement data strategies and systems, to create and maintain the data architecture that will drive various initiatives across the organisation
• Build infrastructure to automate extremely high volumes of data delivery and creatively solve data volume and scaling challenges. Contribute to the design and architecture of innovative solutions to difficult problems.
• Work with team and stakeholders to continually assess and redefine data technology stack to support changing data patterns and business use cases and to bridge the gaps between Data teams and Business by constantly collaborating with all parties to understand data needs.
• Build the infrastructure with IT which is required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and 'big data' technologies.
• Collaborate with IT to source and load a wide range of data across our business into the data lake so that it can be used by analysts and developers to develop data solutions for the business.
• Develop and enhance the data ingestion framework using specified toolsets and will need to understand and continuously seek techniques to ingest data, as well as ensure a high degree of quality and confidence.
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Liaise between technical teams and specialists and business stakeholders, fostering inter-departmental coordination and cooperation.
• Data Governance (Quality, Accessibility, Ownership and Security). Engage with stakeholders to obtain an understanding of their data practices to contract, manage and meet expectations.
• Identify client data quality concerns, conducts root cause analysis and provides feedback to management.
• Become a trusted advisor to stakeholders, and influence decision making by providing an advisory service, guidance and support on data quality practices
• Maintaining a thorough understanding of the business and data strategy.
• Identify opportunities to influence the improvement or enhancement of business processes and methodologies by researching and recommending improvement initiatives and effective ways to operate and add value to the department.
• Train other employees with the division on how to access the Data Ecosystem and how to make the best use of its contents.