Businesses today are swimming in big data, searching for a way to organize, distribute, analyze and gain actionable insights from it. Every day at Robert Half Technology, we interact with people like you – in IT, finance and marketing roles, among others - who struggle to build advanced analytical capabilities. Companies are hiring teams of individuals with skills they haven’t needed to acquire before, and studying the capabilities of various hardware and software to streamline complex processes. We help our clients in manufacturing, technology, retail, finance and other sectors meet their big data needs.
Big data positions we staff include:
- Data Quality Engineer
- Data Engineer
- Data Scientist
- ETL Developer
- Hadoop Engineer
- Master Data Lead
- Technical Architect
Our dedicated big data staffing specialists can quickly meet your time-sensitive staffing needs, nationwide. If you need a dedicated team to manage structured or unstructured data, we can help you build it. Throughout that process, we offer real-time support.
Big data areas of focus include:
- Structured Data
- Unstructured Data
- Data Governance
- In-Memory Computing
- Advanced Analytics (Predictive and Prescriptive)
- Enterprise Data Hub
Learn more about our big data staffing services.
Big Data staffing case study
Client: We worked for a large automobile manufacturer on an 18-month assignment to help develop QlikView applications in a multi-cultural, global purchasing and procurement environment. Robert Half Technology provided a developer with extensive big data expertise to help our client create more efficient processes and improve reporting capabilities.
Process: Beyond meeting the technical demands, the developer we placed quickly discerned that the company culture would significantly influence the design and development of the business intelligence system. Working side-by-side with the principal manager of the department, the SAP consultant and the QlikView development staff, our developer leveraged the existing QlikView data sets already being extracted from SAP. A deeper dive into the 50+ data sets revealed that the existing extract processes wasted a lot of system resources getting data from empty, null or single-value fields.
Results: By modifying the process for one single table extract, the team reduced data collection time by one full hour per day. The team then designed charts and graphs to convey the status of KPIs.
In a three-month beta test, the team collected user feedback, implemented proper revisions, and redeployed the application for minor retesting. The application was then split into two versions for deployment. Both tools, coming from one data set, helped all levels of the department present “a single source of truth.”
The application now reduces the time it takes users to find pain points in daily activities. And it now provides a variety of charts and graphs that clearly illustrate KPIs.