Enterprise Data Solutions Architect

3 weeks ago

Cape Town, Western Cape, South Africa Datonomy Solutions Full time

Job Summary

We are seeking an Enterprise Data Solutions Architect to join our team at Datonomy Solutions in Cape Town. The successful candidate will be responsible for designing, implementing, and managing data pipeline solutions to meet business requirements.

Key Responsibilities:

  • Design and implement data architecture solutions using modern techniques and tools.
  • Develop and maintain ETL procedures for data integration.
  • Collaborate with data engineers and modelers to design, implement, and manage the data pipeline.
  • Develop automated reports for a large user base across our branch network.
  • Monitor and fine-tune the data pipeline, reports, and information layer for optimal performance.
  • Manage hardware and software in the SOH Analytics environment regarding maintenance, patching, upgrades, and access.
  • Implement BI and data management solutions using modern techniques and tools.
  • Engage with technical stakeholders, including data scientists, analysts, and solution architects.
  • Support Data Stewards in establishing and enforcing guidelines for data collection, quality, integration, and processes.

Requirements:

Bachelor's degree in Computer Science, Statistics, Informatics, Information Systems, Engineering, or quantitative fields. National Diploma in IT-related disciplines preferred.

2-5 years of experience in similar environments with relevant tools and techniques.

Tech Skills:

  • Strong understanding of data, data structures, and sources.
  • Application and data engineering background with SQL knowledge.
  • Knowledge of DBMS physical implementation, including tables, joins, and querying.
  • Experience in Database technologies (e.g., SAP, HANA) or Hadoop components (e.g., HDFS, Hive, Spark).
  • BOBJ components knowledge desirable.
  • Object-oriented/scripting languages (Python, Java, Shell) experience.
  • Structured data knowledge (entities, classes, hierarchies, relationships, metadata).
  • Strong Data Engineering background with a focus on high-quality data staging.
  • Understanding of data warehousing principles (Kimball and Vault).
  • Agile development experience.
  • Ability to comply with and manage data assets under governance frameworks.

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