Data Analyst
New
J
JobgetherSecurity & IT
United StatesContractMiddle
Salary48 - 52 USD per hour
Apply NowOpens the employer's application page
Job Details
- Languages
- English
- Required Skills
- PythonSQLBusiness IntelligenceData AnalysisETLMicrosoft Power BIMicrosoft ExcelData visualization
Requirements
- Experience working with SQL, Power BI, Python, data analytics, reporting, and business intelligence in a professional environment.
- Strong SQL skills, including complex queries, joins, aggregations, data validation, and reconciliation.
- Hands-on experience developing Power BI dashboards and data visualizations.
- Proficiency with Python for data analysis, manipulation, automation, or related analytical applications.
- Advanced Excel skills and experience working with data-intensive business processes.
- Knowledge of data quality, data cleansing, data reconciliation, ETL, data integration, relational databases, and data warehousing concepts.
- Experience developing KPIs and metrics and translating analytical results into business insights.
- Demonstrated ability to translate business requirements into practical data and analytics solutions.
- Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Business, or a related field is preferred.
- Excellent written and verbal English communication skills, with the ability to interact professionally and effectively with diverse stakeholders.
- Strong analytical thinking, attention to detail, problem-solving ability, and a commitment to data accuracy.
Responsibilities
- Analyze datasets to identify trends, patterns, opportunities, and risks, translating findings into clear business insights, reports, dashboards, and KPIs.
- Develop complex SQL queries using joins, aggregations, filtering, validation, reconciliation, and other techniques to extract and analyze data from relational databases.
- Design and maintain Power BI dashboards, reports, and visualizations that make key business metrics accessible and actionable.
- Use Python for data analysis, manipulation, transformation, and automation of recurring analytical processes.
- Support data quality initiatives, including data cleansing, validation, reconciliation, ETL, and data integration activities.
- Translate business requirements into effective analytics, reporting, and business intelligence solutions that address stakeholder needs.
- Develop and maintain KPI and metric frameworks to improve visibility into business performance.
- Collaborate with stakeholders and technical teams to understand requirements, investigate data issues, and deliver accurate analytical outputs.
- Communicate analytical findings clearly through written reports, presentations, dashboards, and professional stakeholder interactions.
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