Data Engineer jobs in United States

Purpose of Role:

• To maintain data tools and processes that empower teams across the organization to make informed, strategic decisions.
• To enhance the company's understanding of customer behavior through comprehensive data analysis.
• To contribute to the continuous improvement of data quality and integrity, ensuring reliable and accurate insights.
• To support innovation and product development by providing data insights that inform new features and enhancements.
• To foster a culture of data literacy and self-service analytics within the organization, promoting efficient and effective use of data resources.

Responsibilities:

• Collect, organize, and analyze large datasets to identify trends and patterns that directly inform business decisions and strategies.
• Collaborate with cross-functional teams to understand data requirements and objectives, ensuring data insights are aligned with key business goals and outcomes.
• Assist in the development and maintenance of dashboards and reports for various stakeholders, translating complex data into actionable insights that drive business performance.
• Create and maintain automated report processes to promote a self-service data culture within the company, empowering teams to make data-driven decisions that support business growth and efficiency.
• Utilize Google Analytics to track, report, and analyze website traffic and user behavior to support new product developments and features.
• Support the design and implementation of A/B tests and other experiments.
• Help in data cleaning and preparation to ensure accurate analysis.
• Present findings through clear and concise reports or presentations.
• Stay current with industry trends and best practices in data analytics

Requirements:

• Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, or a similar discipline.
• 1-3 years of experience working as a Data Analyst in the Insurance/Financial Services industry.
• Experience with statistical software such as R or Python.
• Experience with Google Analytics, including understanding of metrics and hands-on experience in generating reports.
• Proficiency in Microsoft Excel; familiarity with data visualization tools such as Qliksense or Power BI is a plus.
• Experience with SQL or other database language is advantageous.
• Strong analytical and problem-solving skills.
• Excellent communication skills, with the ability to present data-driven insights clearly and effectively.
• Detail-oriented with the ability to manage multiple projects and deadlines.