Data Analyst

• Collect, clean, validate, and analyze large datasets from multiple internal and external data sources.
• Develop and maintain dashboards, reports, and visualizations to support business operations and strategic decision-making.
• Analyze business performance, customer behavior, operational metrics, and product performance to identify trends, opportunities, and risks.
• Partner with business stakeholders, product managers, engineering teams, finance, marketing, and operations to translate business questions into data-driven insights.
• Design and execute ad hoc analyses to support business initiatives and executive decision-making.
• Create recurring reports and automate reporting processes to improve operational efficiency.
• Develop SQL queries to extract, transform, and analyze structured data from relational databases.
• Validate data accuracy, identify anomalies, and ensure consistency across reporting systems.
• Define, monitor, and maintain key performance indicators (KPIs) and business metrics.
• Build interactive dashboards using business intelligence tools to communicate insights effectively.
• Perform exploratory data analysis to identify patterns, correlations, and business opportunities.
• Support A/B testing, experimentation, and performance measurement initiatives.
• Collaborate with data engineering teams to improve data pipelines, data models, and reporting infrastructure.
• Document business definitions, reporting logic, metric calculations, and analytical methodologies.
• Present findings and recommendations to technical and non-technical stakeholders through clear visualizations and presentations.
• Identify opportunities to improve business processes using data and analytics.
• Ensure compliance with organizational data governance, security, and privacy standards.
• Stay current with emerging analytics tools, technologies, and industry best practices.

• Bachelor’s or Master’s degree in Data Analytics, Computer Science, Information Systems, Statistics, Mathematics, Business Analytics, Economics, Engineering, or a related quantitative field.
• 3-5 years of professional experience as a data analyst or in a similar analytical role.
• Advanced proficiency in SQL, including joins, window functions, common table expressions (CTEs), aggregations, and query optimization.
• Strong experience with Microsoft Excel, including advanced formulas, PivotTables, Power Query, and data analysis techniques.
• Hands-on experience with business intelligence and data visualization tools such as Tableau, Power BI, Looker, or similar platforms.
• Experience analyzing large datasets and transforming raw data into actionable business insights.
• Strong understanding of data modeling, relational databases, and data warehousing concepts.
• Experience writing complex analytical queries and developing automated reporting solutions.
• Proficiency in Python or R for data analysis, automation, and statistical analysis.
• Experience with data cleaning, validation, profiling, and quality assurance.
• Strong understanding of descriptive statistics, hypothesis testing, trend analysis, and business performance measurement.
• Ability to interpret business requirements and translate them into analytical solutions.
• Experience creating executive dashboards, scorecards, and KPI reporting.
• Strong analytical thinking and problem-solving abilities.
• Excellent communication and presentation skills with the ability to explain technical findings to non-technical audiences.
• Experience working in Agile or cross-functional business environments.
• Ability to manage multiple priorities while meeting project deadlines., * Master’s degree in business analytics, data science, statistics, computer science, or a related discipline.
• Experience with cloud data platforms such as Snowflake, Google BigQuery, Amazon Redshift, Azure Synapse Analytics, or Databricks.
• Experience working with ETL/ELT processes and data integration tools.
• Familiarity with dbt, Apache Airflow, or similar data transformation and orchestration tools.
• Experience using cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
• Knowledge of statistical modeling, predictive analytics, and forecasting techniques.
• Experience supporting A/B testing, experimentation frameworks, and causal analysis.
• Familiarity with data governance, metadata management, and data quality frameworks.
• Experience working with APIs and integrating external data sources.
• Knowledge of version control systems such as Git.
• Experience with scripting and automation using Python, Pandas, NumPy, or Jupyter Notebooks.
• Familiarity with machine learning concepts and model evaluation techniques.
• Experience working in SaaS, fintech, healthcare, e-commerce, enterprise software, or high-growth technology organizations.
• Professional certifications in Tableau, Microsoft Power BI, Microsoft Azure Data, AWS Analytics, Google Cloud Data Analytics, or equivalent certifications.
• Demonstrated ability to influence business decisions through data-driven recommendations.

Pulled from the full job description

• 401(k)
• Health insurance
• Dental insurance
• Visa sponsorship, * 401(k)
• Dental insurance
• Health insurance
• Visa sponsorship