Data Engineer building and scaling client - facing Microsoft Fabric analytics platform to drive revenue and decision - making. Collaborating with teams to develop pipelines, optimize performance, and ensure client satisfaction.
About the role
- Data Engineer developing data pipelines and data assets at Australian Payments Plus. Managing complex datasets and ensuring data integrity using modern data platforms.
Responsibilities
- Build and develop data pipelines to ingest and transform data. Make data available for business use, as per project and operational requirements.
- Ensure data integrity (accuracy, consistency, and completeness), of the data available on the modern data platform (Snowflake).
- Work with data analysts and business users to build and maintain the master data catalogue and system documentation.
- Build and maintain integrations between data lake, data warehouse, real-time streaming platforms, databases, ETL tools, governance, and BI tools.
- Write python scripts to manipulate and transform complex datasets, merge different data sets together, reformat data.
- Create and Publish data flow diagrams and data models.
- Secure data at rest and in Transit through encryption.
- Deploy automated machine learning data models that meet the desired business outcomes.
- Support platform enhancements, capacity management, performance monitoring, troubleshooting and resolution of technical issues.
- Work closely with the team to ensure deliverables and targets are being met.
- Provide second level support on a rotational roster.
Requirements
- Tertiary qualification in engineering, mathematics, computer science, or a related discipline.
- 2+ years of experience in building and maintaining bank grade data infrastructure.
- Experience in transforming and manipulating large and complex datasets.
- Experienced with SQL and NoSQL modern data stores, able to write complex queries and transformations.
- Experienced in implementing data warehousing (snowflake) solutions in large commercial environments and transforming and manipulating large and complex data sets.
- Enjoys working in an agile team and can work on user stories autonomously.
- Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment.
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