Data Analyst - Nomi Health

How you will make an impact

• Use best practices to transform and prepare data for analysis. This includes writing, testing, and deploying transformation code, ensuring data quality and reliability.
• Create and maintain advanced tools and dashboards. Train Operational Analysts on these tools, enabling them to independently run reports and analyses.
• Develop and provide warehouse code optimized for deployment by Data Engineers. This involves working with modern data warehousing tools like Snowflake.
• Ensure the highest quality of data and maintain thorough documentation, making it easier for end users to understand and use the data effectively.
• Serve as a key intermediary between Operational Analysts and Data Engineers, understanding and translating the requirements of both teams to improve data processes and output.
• Leverage SQL/python to extract, transform and analyze various datasets within and across business unitsDesign and implement data models to support analytical needs to empower end-users like data scientists and business analysts and drive a culture of data driven decision makingCreate comprehensive and visually appealing reports, dashboards, and visualizations to communicate findings.
• Implement robust data quality assurance processes to ensure accuracy and reliability of datasets.
• Work closely with cross-functional teams, including business analysts, engineers, and stakeholders, to understand data needs and deliver actionable models & insights.
• Provide training and mentoring to analysts (within and outside of the team)Lead and contribute to the development of best practices for data analysis within the team.

What we are looking for

• This is a hybrid position requiring in-office presence on Tuesdays, Wednesdays, and Thursdays at our Austin office.
• Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field or a Master's degree is preferred.
• Strong academic background in data analysis, statistics, and computer programming.
• Minimum of 1-3 years of experience in a data analytics or engineering role, preferably in a fast-paced and dynamic environment.
• Proficiency in data analysis and visualization toolsExperience with modern data stack tools like dbt, and familiarity with cloud-based data warehouses is a bonusExceptional problem-solving abilities and a dedication to improving data quality at its source.
• Effective communication skills, able to bridge technical and business domains seamlessly.
• Maintain thorough documentation, making it easier for end users to understand and use the output effectively.
• Create comprehensive and visually appealing reports, dashboards, and visualizations to communicate findings.
• Collaborate with stakeholders to understand data requirements and ensure alignment with business objectives.
• Stay informed about emerging trends and advancements in data analytics and SQL technologies.
• Propose and implement process improvements to enhance the efficiency of data-related workflows

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