Data Engineer at SANNE

Role summary:
You will be a part of the Group Data Engineering Squad developing our modern data platform to improve business process, efficiencies, and providing superior client digital services as well as supporting the scaling of our operational model.

As a permanent member of our Data Engineering squad, your focus will be to help implement our Data Strategy by building out our cloud based modern data platform and architecture used to assist with application integrations along with providing a centralised data and analytics platform for downstream data analytics, both internally and externally client facing.

Key responsibilities:

• Working as part of a squad, delivering through agile methodologies;
• Working in collaboration with customers, partners, and peers to identify data requirements;
• Helping break down large problems into smaller iterative steps;
• Contribute to defining the prioritization of your squad’s backlog;
• Build out the modern data platform (data pipelines, data integrations, data preparation, data models, analytical and reporting marts) based on business requirements using agreed design patterns ;
• Help determine the most appropriate tool, method and design pattern in order to satisfy the requirement;
• Proactively suggest improvements where they see issues;
• Prepare our data in order to surface it for use within APIs ;
• Document, support, manage and maintain the modern data platform built within your squad;
• Provide guidance and training to downstream consumers of data on how best to use the data in our platform;
• Support and build new data APIs;
• Contribute to evangelizing and educating within Sanne about the better use and value of data.

Requirements
Skills / experience:

• Excellent communication and interpersonal skills ;
• Critical Thinking and research capabilities;
• Strong problem-solving skills;
• Ability to plan, and manage your own work loads ;
• Work well on own initiative as well as part of a bigger team;
• Working knowledge of Agile Software Development Lifecycles;
• Data Warehousing and Data Modelling ;
• Data Lakes (AWS Lake Formation, Azure Data Lake);
• Cloud Data Warehouses (AWS Redshift, Azure Synapse, Snowflake);
• ETL/ELT/Pipeline tools (AWS Glue, Azure Data Factory, FiveTran, Stitch);
• Data Message Bus/Pub Sub systems (AWS SNS & SQS Azure ASQ, Kafka, RabbitMQ);
• Data Programming languages (SQL, Python, Scala, Java);
• Cloud Workflow Service (AWS Step Functions, Azure Logic Apps, Camuda);
• Interactive Query Services (AWS Athena, Azure DL Analytics);
• Traditional Microsoft BI Stack (SQLServer, SSIS, SSAS, SSRS) ;
• Reporting and visualisation tools (Power BI, QuickSight, Mode ).