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Data Engineers (Multiple)

UNLIMITED HOLIDAYS - EXTRA HOLIDAYS - EXTRA PARENTAL LEAVE - LONG REMOTE PERIOD ALLOWED
Remote: 
Full Remote
Work from: 
Australia
Softtest Pays logo
Softtest Pays Human Resources, Staffing & Recruiting SME https://softtestpays.com/
11 - 50 Employees
About Softtest Pays
Softtestpays is a leading technology and digital talent specialist, with a genuine dedication to candidate, contractor and client service. With operations spanning Australia, we connect thousands of talented people with great jobs every year, providing rewarding opportunities in the best organisations. We partner with our clients across Australia to co-design creative and agile sourcing strategies, to attract skilled talent locally, Candidates come to us because they know we will do everything we can to help them land their dream job – and our contractors are loyal because their dedicated Contractor Care Consultant makes doing business easy. We pride ourselves on operating with the highest ethical standards, and advocate diversity in the workplace. We are proud to be a member of Australian Computer Society – an association dedicated to maintaining an industry-specific ethical code of conduct. We also support Females in IT and Telecommunications, the Australian Network on Disability, and the Project Management Institute. Softtestpays is a Digital talent provider in Australian Digital Industry from 2009 serving Federal, state and private vendors workforce solutions company. Softtestpays become DISP supplier in 2021
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Job description

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Your missions

Australian Citizens residing in Australia with ability to obtain Baseline Clearance only respond.

  • Contract start 18 December 2023 to 30 June 2024, 2 x 12 months.
  • Australian Citizen, Ability to obtain Baseline Clearance, Canberra, Offsite role.

Send your responses to jobs@softtestpays.com

Overview

The Department of Agriculture, Fisheries and Forestry (DAFF) is looking for Data Engineers with strong experience developing Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes across several data and analytics platforms to join its Enterprise Analytics section.

The role will be responsible for design, development and unit testing activities across several data movement and transformation processes within DAFF. These data movement processes are being developed to focus on the preparation of data for use in decision making processes across the department, utilising modern cloud technology (Azure) to enable operational analytics use cases.

The successful candidate will require experience with the following techniques and technologies:

  • MS Azure Stack
    • Data Integration
      • Data Factory
      • SQL Server Integration Services
      • Databricks
    • Data Store
      • SQL Server
      • Data Lake Storage
    • Analytics
      • Azure Databricks
      • Azure Machine Learning
      • ArcGIS Enterprise
  • Development Tools DevOps, Visual Studio, VS Code
  • Data technology solutions sourcing (Oracle, Ingres, Azure, SQL Server), collecting, ingesting and storing
  • Data Preparation
    • Transformation of data into formats tailored to analytics use cases
      • Parquet
      • Delta

Every application requires to address selection criteria as part of application submission.

Essential Criteria Weighting

1. Experience developing ETL/ELT processes for data movement and transformation. 25%

2. Experience preparing data optimised for query performance in cloud computed engines. E.g. Distributed computing engines (Spark) Graph Databases Azure SQL 25%

3. Experience working with Engineering, Storage and Analytics services in cloud infrastructure. 25%

4. Working with multi-disciplinary teams using an Agile methodology 25%

Desirable Criteria Weighting

1. Experience working with Azure Data Factory and Databricks

2. Experience/Knowledge of working with Data Lake and Lakehouses

Required profile

Experience

Spoken language(s):
Check out the description to know which languages are mandatory.

Hard Skills

DatabricksAzure Data FactoryQuery OptimizationDevOps
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