Senior Data Analyst

Summary

Join Later as a Senior Data Analyst and leverage your analytics engineering expertise to build and maintain data models, conduct deep business analyses, and deliver actionable insights. You will translate complex data into business-relevant insights, ensuring data-driven decisions align with company goals. Responsibilities include building and maintaining scalable data models using modern data stack tools, creating dashboards and reports, collaborating with business teams, and designing efficient data structures. The ideal candidate possesses strong analytical and problem-solving skills, expertise in SQL and data transformation tools, and experience with cloud data warehouses. This role offers the opportunity to contribute to a data-driven culture and make a significant impact on the company's success. The position is hybrid, with options for remote work.

Requirements

• Bachelor's or Master's degree in Economics, Statistics, Data Science, Business Analytics, or related field
• 3+ years of experience in data analysis, business intelligence, or analytics roles
• Expert-level proficiency in SQL and experience with data transformation tools (dbt preferred)
• Strong analytical and problem-solving skills with ability to translate data into actionable business insights
• Experience with cloud data warehouses (Snowflake, BigQuery, Redshift, etc.)
• Proficiency in Python or R for statistical analysis and data manipulation
• Experience with data visualization tools (Tableau, Looker, Power BI) and dashboard development
• Understanding of statistical methods and experimental design principles
• Knowledge of data modeling principles and dimensional modeling concepts
• Experience with version control (Git) and analytics code management
• Familiarity with A/B testing platforms and statistical testing methodologies
• Understanding of business metrics and KPIs across different functions (marketing, product, finance)
• Experience working with subscription-based or SaaS business models
• Knowledge of customer segmentation and cohort analysis techniques

Responsibilities

• Translate complex data into business-relevant insights, ensuring that data-driven decisions are aligned with company goals
• Analyze business performance metrics to identify opportunities for growth and improvement
• Build and maintain scalable data models using modern data stack tools (dbt, SQL) to support ongoing analysis
• Create dashboards and reports that track key metrics and communicate results to stakeholders
• Collaborate with business teams across the organization to support strategic initiatives
• Design efficient data structures that enable both ad-hoc analysis and automated reporting
• Conduct deep-dive analyses to understand business performance, user behavior, and market trends
• Develop hypotheses and design analyses to answer key business questions
• Present findings and recommendations to stakeholders, including senior leadership
• Partner with business teams to define KPIs and success metrics for various initiatives
• Perform exploratory data analysis to uncover new opportunities and insights
• Build and maintain data models using dbt or similar tools to support scalable analytics
• Create reusable data assets and standardized metrics definitions
• Implement data quality checks and monitoring to ensure analysis accuracy
• Work with data engineering teams to optimize data pipeline performance
• Design data structures that balance analytical flexibility with performance
• Partner with analysts and business users to understand reporting and analysis needs
• Create self-service analytics capabilities through well-designed data models and documentation
• Provide training and support to help teams effectively use data assets
• Build automated reporting solutions and standardized metrics definitions
• Act as the technical liaison between data engineering and business teams
• Present data architecture decisions and recommendations to technical and non-technical stakeholders
• Work closely with data engineering to ensure compliance and best practices
• Support ad-hoc analysis and data requests from various business teams

Benefits

$ 80,000- $100,000 USD