Solution Architect – Data Engineering
As a recognized data engineering authority, the Solution Architect collaborates in data engineering standards & controls and creates the data engineering architecture for the target environments to deliver data pipelines into the bigger Business Intelligence environments. Extensive subject matter knowledge of data engineering is essential, as well as ETL, relational databases, data warehousing, and big data. The solution architect will collaborate closely with the data, integration, and analytics teams.
- 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).
- 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
- 3+ years Proven experience with data engineering in a cloud environment (AWS/Azure/Google) as well as on-premise.
- 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)
Define and continuously improve the data engineering architecture framework and modeling standards:
- Define a structured data engineering architecture approach and methodology for capturing the key views of the enterprise.
- Architect the next-generation Big Data analytics framework developed on a group of core technologies.
- Align to the enterprise data reference architecture in support of the enterprise and regulatory information governance needs such as Information Security, Enterprise Information Management, POPI, PCI, etc.
- Identify, define, and communicate standards, guidelines, formats, meta-models, policies, best practices, and governance practices for Data Engineering architectures and designs.
- Ensure that the Data Engineering approach integrates into the methodologies and processes of the rest of the Enterprise Architecture team.
- Stay abreast of best practices and/or new developments in Data engineering and related disciplines and drive adoption as deemed appropriate.
Analyze the inputs and outputs of BI and analytics and create related Data engineering architectures and designs for the baseline (“as is”) and target (“to be”) solution architectures.
- Coordinate with system analysts, development teams and DBAs to ensure creation of physical database and an optimal implementation of the data engineering design.
- Define data engineering architecture governance processes and quality compliance criteria.
- Perform quality assurance checks on Data engineering Architectures and Designs and enforce quality compliance criteria to set policies and standards.
- Perform quality checks on existing Data Engineering Architectures and Designs to identify potential business risks areas and make re-engineering recommendations.
- Ensure Data engineering security conforms to Information Security Governance policies and standards.
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.
- Define and develop the overall data engineering architecture landscape in partnership with the Domain Architect, Data Analytics team and other Solution Architects.
- Review proposed solution architectures ensuring alignment with architecture principles, the architecture framework, cloud reference architectures, set technology standards and identify critical gaps, and recommend improvements.
- Give guidance and advice to peers in respect to data engineering solution designs ensuring the designs conform to industry best practices and standards
Knowledge & Skills:
- Strong analytical, problem-solving and logical skills
- Excellent team-working, interpersonal skills
- Delivery of compelling presentations to all levels of stakeholders and excellent communication and relationship building skills
- Develop of proposals and excellent written communication & presentation skills
- Excellent organization and facilitation skills Strong conflict management skills