Big Data Practice Manager

Is innovation part of your DNA? Do you want to enable a connected future for people, organizations, and society?

Join our growing global NTT team and you’ll be part of the world’s largest ICT company (by revenue). We’ve combined the capabilities of 28 remarkable companies to become one, leading technology services provider. Together, we help our people, clients, and communities do great things with technology to create a more secure and connected future. We employ 40,000 people across 57 countries. By bringing together the world’s best technology companies and emerging innovators, we work together to deliver sustainable outcomes to businesses and the world. Innovation is part of our DNA. We believe it’s key to what makes us different. So, we strive to move forward, challenge the status quo, and drive excellence through the technologies we integrate and the services we deliver around the world. The result is connected cities, connected factories, connected healthcare, connected agriculture, connected conservation, connected mobility, and connected sport. Together we enable the connected future.

Want to be part of the team?

 

In this role, you will be working with our dedicated client partners to engage with our clients to understand their challenges and opportunities and position solutions and services.  You will also design, manage, deliver and implement complex data and information management platforms in areas such as business intelligence, machine learning, data mining, complex data analytics, taking a solution from strategy through implementation to managed service.

You will work in some of the most challenging and exciting domains across government and industry, grappling with the most interesting and varied data sets Australia has to offer. You will be undertaking complex research in the application of data governance, data analytics and science techniques to industry business problems along with designing data management and analytics processes and models to deliver insights and meet business outcomes.

A key part of this role will be working with the Director for Data & Analytics to shape the go-to-market, including service offers; capability and training plans; marketing and vendor partnerships.

 

Responsibilities:

  • Designing, architecting, and implementing complex real-time and batch data analysis solutions and services in business intelligence, predictive and prescriptive analytics, data science, data management, and information management, utilizing Agile (Scrum) frameworks
  • Designing, developing and implementing machine learning algorithms to create, coordinate and deploy information and analytics solutions
  • Providing technical guidance as SME and hands-on delivery to team members across multiple clients and engagements
  • Building relationships with clients and relevant vendors (i.e. Marklogic, Cloudera, Splunk, etc) identifying opportunities for organizational transformation and data design improvement
  • Leading and delivering business development activities in the data and analytics space
  • Managing multiple client engagements and leading several teams
  • Managing and mentoring staff 

 

Skills & Experience:

  • Proven experience producing design artefacts, prototypes, process models, service catalogs, and service designs, and dealing with complex data sets, data platform/techniques, and analytics solutions
  • Proven experience designing across multiple big data technologies, such as Cloudera, Marklogic, Neo4j, Splunk, Cassandra, Spark, Kafka, etc.
  • Experience designing data mining and analytics solutions with a range of software and statistical development platforms (such as R, Python, etc).
  • Experience designing across multiple data visualization technologies, including Qlik & Tableau
  • Well-developed skills using SQL for data manipulation and query of large datasets
  • Excellent understanding of a range of predictive and descriptive modeling techniques
  • Solid knowledge in popular techniques and algorithms for data mining and machine learning, such as classification, clustering, outlier detection, association rules, time series analysis, text mining, natural language processing, and social network analysis