What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 3+ Years operational experience of Software and Data Architecture Patterns
- 3+ Years operational experience of Python Data Science Development
- 3+ Years operational experience of Data Warehousing, Data Modelling, Data Transformation and Data Quality
- 3+ Years operational experience of NoSQL Development (BigQuery / MongoDB)
- 3+ Years operational experience of Distributed Data Warehousing, Query Optimisation, Data Modelling, Role / User Management, BigQuery Monitoring & Alerting
- Operational experience of Data Reporting Tools, Apache Superset, Tableau, BI
- Operational Experience of Apache Airflow, DAG Management, Airflow Monitoring & Alerting
- Familiarity with Cloud APIs and SDKs, Unit Testing Strategies
- Strong understanding of Agile/Scrum methodologies
- Strong diagnostic/troubleshooting skills for complex enterprise systems
- Able to quickly learn and work with new languages and technologies
- Ability to build strong, collaborative working relationships
- Open attitude to sharing ideas, knowledge, and information
- Can work in a challenging, fast-paced environment
Day to day
- Leads, designs, develops, and provisions data warehousing, data orchestration, data transformation, and ETL solutions aligning with industry best practices and team standards.
- Manages the availability and performance of the data platform through monitoring tools, ensuring quick interventions for operational issues.
- Establishes standards for technical delivery, ensuring best practices in version control, testing, and deployment.
- Ensures data security compliance across multiple states and regions.
- Leverages multi-cloud services for optimal data management and processing.
- Develops strategies for disaster recovery and business continuity.
- Designs and implements business intelligence solutions in collaboration with stakeholders.