Senior Data Analyst, Go-To-Market
New
J
JobgetherHealthcare Technology
Based in United StatesFull-TimeSenior
Salary140,000 - 160,000 USD per year
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Job Details
- Experience
- 5+ years
- Required Skills
- AWSPythonSQLMicrosoft Power BISalesforceSnowflakeTableauAirflowdbtLooker
Requirements
- Bachelor’s degree in a quantitative, technical, business, or related field, or equivalent professional experience.
- 5+ years of experience in data analytics, business intelligence, reporting, or a related analytical role.
- 5+ years of experience using Python for analytics, automation, or data science projects.
- Advanced SQL skills, including data extraction, transformation, validation, and performance optimization.
- Experience with business intelligence platforms such as Tableau, Looker, Power BI, or similar tools.
- Strong AI fluency, including experience using AI tools or agents to automate workflows, improve analysis, and increase productivity.
- Experience supporting analytics needs across multiple business functions such as marketing, sales, finance, product, or customer success.
- Strong understanding of data quality practices, including validation, documentation, and reporting accuracy.
- Ability to transform complex analysis into clear business recommendations for technical and non-technical audiences.
- Excellent communication, organization, and stakeholder management skills.
- Ability to work effectively in a fast-moving environment with changing priorities and limited direction.
- Collaborative, entrepreneurial mindset with strong problem-solving abilities and ownership.
Responsibilities
- Partner with cross-functional teams including Marketing, Finance, Product, Sales, Medical Affairs, and Customer Success to understand business needs and deliver actionable insights.
- Analyze large datasets to identify trends, patterns, risks, and opportunities that support business growth and operational improvements.
- Define data requirements and improve reporting processes to ensure accurate, consistent, and scalable analytics.
- Develop, optimize, and automate data pipelines using SQL, Python, AI tools, and modern data engineering technologies.
- Build and maintain interactive dashboards and reporting solutions that enable self-service analytics across teams.
- Identify opportunities to streamline workflows, reduce manual efforts, and improve overall data efficiency.
- Translate analytical findings into compelling visualizations, presentations, and recommendations for technical and executive audiences.
- Collaborate with analysts, data scientists, and engineers to enhance data quality, reporting accuracy, and analytical standards.
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