Data Engineer

Data Engineer, Retail Business Intelligence

• Contract with extension potential C2H
• Hybrid in Houston, TX
• W2 only

Join the Retail Business Intelligence team to strengthen the BI capabilities of company retail.

• Gather large and complex data sets to meet business requirements.
• Re-designing data marts for scalability and optimization.
• Ensure data architecture supports existing and future requirements of evolving business model.
• Identify, design, and implement process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Create and maintain documentation for each step in the data lifecycle.
• Develop and maintain operational dashboard and executive-level reporting using tools like Tableau, or Power BI.
• Interact with functional business units to analyze, gather, and prioritize business and reporting requirements.
• Partner with the Enterprise Data and Analytics leaders and teams to manage the key data processes, tools, and architectures needed to deliver confidence in regular reports.
• Collaborate with Enterprise Data and Analytics team to implement data management, data quality best practices and standards.
• Partner with business leaders to develop, monitor, and report on marketing tests for new or enhanced products and campaigns.
• Provide ad hoc report for Retail organization for experiments in market.
• Hands on development of data models in Oracle, AWS and data visualizations.
• Formulate and provide status updates on project plans and schedules to meet goals/objectives.

• Bachelor's degree
• Gas or power industry experience with knowledge of the retail electricity market is a must
• 3+ years in one of programming languages like SAS/R/Python is a must
• 4+ years of professional experience in business intelligence and data analysis
• 3+ years of SQL
• 2+ years building dashboard and using Tableau/Power BI
• 1+ years in AWS and big data distributed ecosystems
• Experience with dimensional modeling and improving data reliability and data quality
• Data models and data pipelines
• Good understanding of cloud technologies
• Good understanding of relational and non-relational databases
• Experience working with large datasets
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• A successful history of manipulating, processing, and extracting value from large, disconnected datasets
• Strong organizational skills and comfort interacting with different lines of business, IT, and senior management
• Comfortable with ambiguity; ability to work with incomplete data or open-ended questions, and translate into actionable items