Address
Form of workWhat you'll be doing:
The is expected to assume the following key responsibilities plus any other reasonable duties as required:
- Act as bridge between Architecture and delivery teams by creating HLD and LLD as well as contributing to architecture governance by proactively discovering architecture pitfalls.
- Design and implement robust architecture for managing large-scale data and automating complex processes.
- Provide guidance and mentorship to engineering teams on best practices in data management, integration and automation.
- Evaluate and integrate new technologies and software engineering tools into existing systems and data landscape.
- Lead the design and implementation of data warehousing, ETL processes, and data analytics platforms.
- Perform assessments and detailed analysis to build POCs and Minimum Viable products using cloud services/capabilities for messaging and serverless workflow orchestration.
- Evaluate and assess out of the box cloud services categorically event driven, messaging and API capabilities that can be leveraged for Enterprise integration Architecture
- Creating quality Artefacts demonstrating critical architecture domains for technical as well as non-technical audience
- Stay abreast of industry trends and advancements in data architecture and automation technologies.
Qualifications
Hands-on experience on architecting modern data and integration solutions to help real-time data exchange and automation.
- Proven experience as a Technical Architect, Data Architect, or similar role, with a focus on data management, integration and automation.
- Strong expertise in database technologies, ETL tools, data warehousing (e.g. AWS Redshift)
- Expertise in conceptual, logical, and physical data modelling, data warehousing, and data lake design principles.
- Proficiency in programming languages such as Python
- Experience in establishing data governance frameworks, data quality standards, metadata management, and data lineage practices.
- Proficiency in automation and orchestration tools (e.g., GitLab CI/CD) and an understanding of Infrastructure as Code (IaC) principles.
- Knowledge of security best practices, data encryption, access control, and familiarity with compliance requirements relevant to data management (e.g., GDPR).
- Familiarity with machine learning algorithms, generative AI, data analytics platforms, and tools (e.g., TensorFlow, PyTorch, Tableau, Power BI) is a plus.
- Excellent technical, analytical skills
- Strong communication and interpersonal skills
- Team player and able to work effectively at all levels of an organisation with the ability to influence
- Working knowledge of Functional monitoring tools and Custom metrics.
- Understanding good coding standards, industry standard best practices
- Bachelor's degree in information technology is preferred
