Senior Data Analyst
New
E
Energy SolutionsEnergy solutions
Senior Data Analyst (Remote - US)Full-TimeSenior
SalaryThe salary range for this role is $105,000 - $130,000, with a target compensation of $105,000 - $123,500 based on experience and qualifications.
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Job Details
- Experience
- 8 years of experience in data analytics, business intelligence, statistical analysis, data modeling, reporting, or a related field
- Required Skills
- PythonSQLBusiness IntelligenceSalesforceData visualizationData modelingWorkdayData analytics
Requirements
- Hold a bachelor’s degree in Data Analytics, Computer Science, Mathematics, Statistics, Engineering, Business, Economics, or a related field, or have equivalent relevant experience.
- Have 8 years of experience in data analytics, business intelligence, statistical analysis, data modeling, reporting, or a related field.
- Have experience managing complex data analysis or business intelligence workstreams involving multiple stakeholders and data sources.
- Have experience building and optimizing dashboards, reports, analytical models, queries, and data workflows.
- Be able to translate complex analytical findings into clear business insights and recommendations.
- Have experience mentoring analysts or providing technical guidance and review.
- Have experience collaborating with business stakeholders and data engineering or technical teams.
Responsibilities
- Manage data analysis and business intelligence workstreams supporting revenue forecasting, profitability review, operational planning, and business performance evaluation.
- Build analytical models, queries, and data sets using SQL, Python, and other approved analytical tools.
- Build dashboards, reports, and data visualizations for technical and nontechnical audiences.
- Coordinate analytical dependencies involving business teams, data engineers, and systems such as Salesforce and Workday.
- Mitigate data-quality and reporting risks through validation, investigation, documentation, and stakeholder coordination.
- Resolve data issues in line with data governance, security, documentation, and quality practices.
- Create reusable queries, reports, dashboards, analytical methods, documentation, and data-quality controls.
- Implement approved analytical process improvements and automation opportunities within assigned work.
- Coach team members on SQL, Python, data visualization tools, and analytical methods.
- Review analytical work and provide constructive technical feedback.
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