Job Description

Requirements:

• Degree in Information Systems / B Sc Computer Science (or similar)
• 5 + years working experience within the IT industry
• 5 years Leadership role in an Information and Data analysis environment desirable
• 5+ years Experience with IT projects from an Information and Data architecture and design perspective (SDLC).
• 2 - 3 years Knowledge of various architecture frameworks including TOGAF and Zachman frameworks (TOGAF certification would be a distinct advantage)
• 5+ years Demonstrable knowledge of Data Engineering Architecture and familiarity with various architecture viewpoints (business, applications, data, and technology architectures) is required.
• 5+ years Proven experience creating data engineering solutions, building and maintaining reliable and scalable ETL on big data platforms as well as experience working with varied forms of data infrastructures
• 5+ years Experience in working with Data Ops and/or Dev Ops Frameworks
• 3+ years Knowledge of implementing future-fit Data Engineering technologies and capabilities such as APIs, API Portals, and Lakehouse architectures.
• 5+ years Proven Experience in using scripting languages such as Python and SQL to create, manage, manipulate data pipelines and - sets
• 3+ years Proven experience with data engineering in a cloud environment (AWS/Azure/Google) as well as on-premise.
• 5+ years Experience in solution architectures, system analysis and design, data modeling and application development methodologies
• 5+ years Experience with data profiling, data cleansing/quality, performance issues, reporting and data analysis
• 5+ years Experience in database and data management (Data Replication, Backup and Recovery, DBMS Scaling techniques, SOA, ODS/OLTP vs Data Warehouse/OLAP/VLDB)
• 5+ years Experience in various data modeling paradigms (dimensional, data vault, normalized, NoSQL)
• 3+ years Experience in implementing and using EA tools and EA meta-model definition (ARIS Preferable/ or Sparx Enterprise Architect)
• 2+ years Retail industry experience with an understanding of retail business processes and the information and data requirements of these processes.

KPAs:

• Define and continuously improve the data engineering architecture framework and modeling standards
• Define and create solution level data engineering architecture models that enable specific BI and analytics requirements.
• Provide expert data engineering guidance, ensure solution architectures and designs are in line with the data engineering technology standards and conduct architecture and design reviews as part of the Architecture Review Committee.

Please note that prospective employees will be subject to security vetting. Should you not hear from us within 10 working days, please consider your application as unsuccessful.

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