As a Senior Data Analyst with 5+ years of demonstrated experience, you will transform complex datasets into actionable insights, build and maintain analytics infrastructure, and partner with cross-functional teams to drive data-informed decision-making and product improvements. Youll own the end-to-end analytics lifecyclefrom data modeling and dashboard creation to experimentation and KPI developmentensuring that our stakeholders have timely, accurate information to optimize operations and enhance customer experiences.
Key Responsibilities
Using the available data and data models, perform analyses that answer specific data questions and identify trends, patterns, and anomalies
Build and maintain dashboards and reports using tools like Looker and Databricks; support monthly reporting requirements
Collaborate with data engineers, data scientists, and product teams to support data initiatives for internal use as well as for end customers
Present findings and insights to both technical and non-technical audiences provide visual aids, dashboards, reports and white papers that explain insights gained through the multiple analyses
Monitor select data and dashboards for usage anomalies and flag for upsell and cross-sell opportunities
Translate business requirements into technical specifications for data queries and models
Assist in the development and maintenance of databases and data systems; collect, clean, and validate data from various sources to ensure accuracy and completeness
What You Need
Were seeking an experienced analyst who thrives in an agile, collaborative environment and enjoys tackling technical challenges.
Minimum Qualifications
Bachelors degree in a quantitative field (e.g., Mathematics, Statistics, Computer Science, Economics, Business Analytics)
4+ years of experience in a data analysis or business intelligence role
Proficiency in SQL, Python, Scala, Pyspark, and other data analyst languages and standards for data querying and manipulation
Experience working in a collaborative coding environment (e.g., GitHub)
Experience with data science, analysis, and visualization tools (e.g., Databricks, Looker, Spark, Power BI, plotly)
Strong analytical and problem-solving skills with attention to detail
Ability to communicate insights clearly and concisely to a variety of stakeholders
Understanding of data lakes and data warehousing concepts and experience with data pipelines
Knowledge of business systems is a plus (e.g., CRMs, demand gen tools, etc.
