Data Analyst – SQL, Power BI & Python in New York at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Analyst – SQL, Power BI & Python based in United States.

This is a remote, 12-month contract opportunity for a data professional who can turn complex information into actionable business insights.
You’ll work across data analysis, reporting, visualization, and business intelligence to support informed decision-making.
The role combines advanced SQL, Power BI, Python, and Excel to uncover trends and build meaningful performance metrics.
You’ll contribute to data quality, cleansing, reconciliation, ETL, and integration initiatives across relational and analytical data environments.
A key part of the role is translating business needs into practical analytics and reporting solutions.
You’ll collaborate with diverse stakeholders in a professional, data-driven environment where accuracy and clear communication are highly valued.
This is an opportunity to make a measurable impact through reliable data, compelling dashboards, and insight-driven recommendations.

• 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.

• 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.

• Remote work arrangement.
• 12-month contract opportunity.
• Expected base compensation of $48.00–$52.00 per hour.
• Compensation is determined based on relevant skills, training, experience, education, market factors, and applicable certifications or licensure.
• Competitive benefits package in addition to base compensation.
• Opportunity to work on meaningful data analytics, business intelligence, and reporting initiatives.
• Exposure to SQL, Power BI, Python, ETL, data quality, and modern analytics practices.