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Data Engineer

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We are looking for an experienced Data Engineer to support a data migration and integration programme within a relatively low maturity Azure environment.

The role will focus on designing and building robust data pipelines, migrating data from a wide range of legacy and enterprise source systems, and establishing scalable data flows into Azure Data Lake and Databricks. A key part of the role will also involve integrating data into a proprietary data transformation solution where applicable.

Key Skills & Experience

  • Azure Data Engineering
  • Azure Data Factory (ADF)
  • Azure Data Lake
  • Databricks
  • Building ETL / ELT pipelines
  • Large-scale data migration and integration
  • Oracle and/or Oracle Fusion data sources
  • SharePoint data extraction and integration
  • Working with multiple and varied source systems
  • Data transformation, mapping and validation
  • Designing data pipelines in environments where architecture and processes are still developing

Key Responsibilities

  • Design, build and maintain data migration and ingestion pipelines within Azure.
  • Support the setup and development of the Azure Data Lake environment.
  • Build integrations between source systems, Azure Data Lake and Databricks.
  • Develop and manage pipelines using Azure Data Factory (ADF).
  • Extract and migrate data from a variety of source systems, including:
  • Oracle
  • Oracle Fusion
  • Informatica
  • SharePoint, which will be an initial priority
  • Additional enterprise and legacy systems as the programme develops
  • Help define scalable data ingestion, transformation and migration patterns for future source systems.
  • Support data quality, validation and troubleshooting throughout the migration process.
  • Work closely with technical and business stakeholders to understand source data, target structures and transformation requirements.
  • Help improve the overall maturity of the Azure data environment, introducing appropriate engineering standards and best practices.


Skills

See also

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