Please respond to the job if you have a valid work visa and residing in Australia.

• Contract start ASAP to 30 June 2023, Possible extensions.
• Eligible to work in Australia, Brisbane, Hybrid (3 days on-site, 2 days off-site) role.

Send your responses to jobs@softtestpays.com

Overview

About the Role

This role is seeking a SQL developer as part of our Microsoft Azure data warehouse team. The lead developer will work within an Azure DEVOPS environment, actively developing stories as prescribed from the product backlog to improve our customer experience. Technical requirements are listed below:

Position Description

SQL Developer

Microsoft Platform knowledge on Azure, Power BI, SQL Server, the Microsoft BI and hybrid/cloud stack and offerings

Business Intelligence design and implementation using Microsoft Business Intelligence stack (SSIS, SSAS and SSRS)

Ideally SQL Server experience

PowerBI using tabular models, Power Pivot, Power BI Desktop & Power query

SSAS tabular data model design, optimisation and query using DAX

SSIS design and development of ETL workflows, SSIS automation

Azure Databricks and Azure Data Factory experience exceptionally advantageous

Client engagement including prototype reviews and requirements gathering

Data warehouse knowledge

Administrative duties 5%

Administrative duties as needed.

What you will bring to the role:

Demonstrated experience working on Business Intelligence\Data Warehouse platforms and solutions

Ability to work in complex organisational environments (i.e. matrix) and with remote teams

Ability to plan work to meet deadlines

A keen focus on minimising the impacts that a technology project can have on the end user experience

Customer focus and strong understanding of business context

Be a self-starter and have an ownership mentality

Highly Desirable Skills

Reporting and Business Intelligence - A primary consumer of data assets in the enterprise

Data Governance and Quality - Building integrity and trust in data

Information Security - Confidentiality, integrity and availability of data

DataOps - Automation practices and tools which accelerate delivery of data assets

Non-warehouse Data Architectures - Data lakes, data virtualization