Data Engineer

Application closing date: Thursday, 2 December 2021, 06:00 pm (in Canberra)

Estimated start date: Mon Jan 03 2022

Location of work: Australian Capital Territory

Length of contract: To 30 June 2022

Contract extensions: 2 x up to 12 months options to extend

Security clearance: Must have current baseline clearance (Must be Australian Citizen)

Rates: $120 - $140 per hour (inc. super)

The Department of Agriculture, Water and the Environment (DAWE) is looking for an experienced Data Engineer with experience developing Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes across several data and analytics platforms.

The role will be responsible for design, development and unit testing activities across several data movement and transformation processes within DAWE. These data movement and transformation processes are in the process of being uplifted to Microsoft Azure and the successful candidate will require experience using the following technology:
1. MS Azure Stack
a. Data Integration
i. Data Factory
ii. SQL Server Integration Services
b. Data Store
i. SQL Server
ii. Synapse Analytics
iii. Blob/File Storage
iv. Cosmos DB
c. Analytics
i. Azure Databricks
ii. Stream Analytics
2. Development Tools – DevOps
3. Data technology solutions – sourcing (Oracle, Ingres, Azure, Wintel Server Network file shares), collecting, ingesting and storing

Please note, flexible working arrangements are supported by the Department of Agriculture, Water and the Environment while COVID restrictions or staged return to workplace conditions are in place, but under normal circumstances there is an expectation that the role will be undertaken onsite in Canberra.

Essential Criteria

• Experience developing ETL/ELT processes for data movement and transformation.
• Experience developing data storage layers optimised for query performance
• Azure Cloud technology experience working with Engineering, Storage and Analytics services.
• Working with multi-disciplinary teams using an Agile methodology

Desirable Criteria

• Experience working with Azure Data Factory and Databricks
• Experience work with Data Lake