Royal Dutch Shell PLC, commonly known as Shell, is a British-Dutch multinational oil and gas company headquartered in the Netherlands and incorporated in England. It is one of the oil and gas “supermajors” and the third-largest company in the world measured by 2018 revenues
Process Data Engineer -Technical Data
Finance & Data Operations SSW (Subsurface and Wells) Team is tasked with delivering tangible value to Upstream business units within Shell through Analytics driven decision making.
This position is part of Finance & Data Operations – Subsurface and wells (Technical Reporting) team delivering advanced analytics projects for upstream businesses within Shell
Incumbent is responsible for supporting the development of technical models for projects collaborating with different business stakeholders & other partners and working across a range of technologies and tools.
The ideal candidate should have good background in data warehousing concepts and Spotfire/ Microsoft Power BI reports development
Enhances organization reputation by accepting ownership for accomplishing new and different requests; exploring opportunities to add value to job accomplishments
- Degree/master’s in information management (degree in relevant Oil & Gas discipline an advantage). A keen desire and ability to learn new things and assimilate knowledge will be essential.
- 2-3 years of experience building analytical models desirable.
- Experience in Spotfire/Microsoft Power BI professional for loading data from databases, creating visualization and filters.
- Ability to transform business level requirements to efficient dashboards and visualizations.
- Good knowledge of Spotfire/Microsoft Power BI architecture and different servers.
- Experience in creating customized visualizations, custom expressions, inserting rows/columns, Data on demand, property controls, text areas, properties of different charts.
- Should have knowledge on Data Warehousing.
- Should be an expert in scripting language like iron python.
- Proficiency in advanced features like multiple filtering scheme, custom expression, multiple marking, multiple data table and relation between multiple data table, property control etc
- Work closely with QA, Data architects, to develop dashboards and understand user behaviors, log analysis, and known software bugs.
- Troubleshoot visualizations in increasing the load efficiency in dashboards