Data Warehousing Director directs the team responsible for the design, implementation, maintenance, and support of data warehouse systems and projects. Has overall responsibility for the development of data warehouse strategy, architecture and standards that meet business needs. Being a Data Warehousing Director ensures that new data platforms can be successfully integrated with existing warehouses, and that data warehouse systems fully support organization-wide data initiatives. Requires a bachelor's degree. Additionally, Data Warehousing Director typically reports to senior management. The Data Warehousing Director manages a departmental sub-function within a broader departmental function. Creates functional strategies and specific objectives for the sub-function and develops budgets/policies/procedures to support the functional infrastructure. To be a Data Warehousing Director typically requires 5+ years of managerial experience. Deep knowledge of the managed sub-function and solid knowledge of the overall departmental function. (Copyright 2024 Salary.com)
We are a customer-obsessed, “one stop shop” for all things data-related. We are deliberately narrow in our focus areas but we go deep in each of them. We provide solutions, services and training in the data strategy, data governance, data security, data management, data classification, data wrangling, data lake, data analytics, data visualisation, artificial intelligence, machine learning and IoT areas. Our solutions and services help transform customer organisations by teaching them how to turn their data into insight
We build on AWS, using the latest AWS services, best practices and reference architectures. We deliberately focus on large public sector customers that are data-heavy but insight-light – federal & state government departments, universities, public sector agencies, public health organisations, and public utilities.
We are an AWS Advanced Consulting Partner and an AWS Public Sector Partner, working towards our Data & Analytics and Government competencies. We are also a registered technology supplier to the Federal, New South Wales, Victorian and Western Australian governments and we have a Master Services Agreement in place with AWS Professional Services.
Your impact
As a Data Analyst, you will play a key role in working with customers to understand their business requirements, map these to their data capabilities, liaise with our internal Data Engineers to design and build elegant solutions, then partner with our customers to deploy those solutions in a way that allows them to turn data into insight. You will have 2-3 years’ experience working as a Data Analyst (or similar role) on data-related solutions, preferably using AWS, and will be comfortable working with business analysts, data visualisers, data engineers and data scientists, to enable customers to solve their data-related challenges.
You will relish the opportunity to innovate, evolve and challenge existing assumptions and to develop the data-related requirements that feed into the design of solutions that solve real-world problems for customers. Your experience with large-scale data challenges and ability to analyse them as input into reliable, scalable cloud-based solutions, will see you thriving in this role!
Expectations
Technical Requirements:
2 years of:
o Hands on, practical experience, in and around data-related solutions
o AWS experience (Desired)
o A basic understanding of software development tools and methodologies
o Data analysis experience
o Experience producing quality documentation and written communications
· Familiarity with DevOps tools such as Bitbucket, Bamboo, Jenkins or Ansible
· Some experience with both writing and interpreting SQL queries.
· Experience building reports and dashboards using BI tools such as Tableau, PowerBI or Amazon QuickSight.
· A basic understanding of Infrastructure as Code, especially AWS Cloudformation.
· Some programming skills in one or more of the following languages: Python, Java, Node.js, .Net, PHP.
· A basic understanding of data ingestion and transformation pipelines.
· A basic understanding of fundamental data concepts including databases, data schema, data classification, data security, data governance, data analysis, data transformation, data engineering and data science.
· A basic understanding of fundamental networking concepts.
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