hackajob
Senior Data Architect / Data Solution Architect
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As a Senior Data Architect, you will be expected to take an architecture lead role on our client’s solution delivery engagements, with high levels of customer engagement. This will involve ongoing analysis of business requirements throughout the lifetime of the service. Candidates will have a strong understanding of data architecture and analytics design and project delivery life-cycles with an emphasis of working in client-facing environments.
Typically, The Role Will Involve The Following
- Translating Business requirements to technical solutions and the production of specifications,
- Designing and implementing business intelligence & modern data analytics platform technical solutions,
- Data architecture design and implementation
- Data modelling,
- ETL, data integration and data migration design and implementation
- Master data management system and process design and implementation,
- Data quality system and process design and implementation,
- Major focus on data science, data visualisation, AI, ML,
- Documentation of solutions (e.g. data modelling, configuration, and setup etc.) including HLD and LLD,
- Working within a project management/agile delivery methodology,
- Managing Team Members on a day to day basis,
- Managing technical delivery of solution,
- Strong stakeholder management and communication skills
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Qualifications
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- Hands-on experience with data solution architecture, design and rollout.
- Hands-on experience with business intelligence tools, data modelling, data staging, and data extraction processes, including data warehouse and cloud infrastructure.
- Experience with multi-dimensional design, star schemas, facts and dimensions.
- Experience and demonstrated competencies in ETL development techniques.
- Experience in data warehouse performance optimization.
- Experience on projects across a variety of industry sectors an advantage,
- Comprehensive understanding of data management best practices including demonstrated experience with data profiling, sourcing, and cleansing routines utilizing typical data quality functions involving standardization, transformation, rationalization, linking and matching,
- Good knowledge of Databricks, Snowflake, Azure / AxoWS / Oracle cloud, R, Python.
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