Sr. Data Analyst

Location: Dallas or Miami- hybrid - ONSITE Interviews

Key Responsibilities

• Conduct more complex data analysis and develop insights that support business objectives.
• Create and maintain more advanced reports and dashboards for various stakeholders.
• Build and maintain dbt models (staging, intermediate, mart layers)
• Write and optimize SQL for data transformation and analysis
• Design and enforce data testing/validation (dbt tests, source freshness checks)
• Maintain documentation (dbt docs, data dictionaries, lineage)
• Partner with stakeholders to translate business questions into metrics/dashboards
• Manage version control workflows for dbt projects (Git-based)
• Monitor data quality and troubleshoot pipeline failures.
• Proficient in advanced data cleaning techniques, such as normalization, handling categorical variables, and merging datasets.
• Experience using tools like Python (pandas, NumPy) or R for complex data manipulation
• Ability to create interactive dashboards (Power BI), use calculated fields, and design complex visualizations that tell a compelling data story.
• Knowledge of best practices in data visualization and experience with custom visualizations.
• Understanding of how to create and maintain data models to support business reporting needs.
• AWS, Snowflake, Azure
• AWS Glue, AWS Appflow, Lambda, S3, Funnel, Athena
• Support CI/CD workflows for dbt deployments
• Exceptional ability to influence and engage senior leaders with data-driven insights.
• Expert in resolving complex, high-stakes problems with innovative solutions.
• Extensive experience with data pipeline orchestration tools (e.g., Apache Airflow, Luigi) and data integration platforms (e.g., Apache NiFi, Glue).
• Skilled at supporting and managing multiple projects and meeting deadlines
• Experience with statistical analysis and predictive modeling.
• Identify trends, patterns, and anomalies in data sets and present findings to senior analysts.
• Contribute to the development of best practices for data management and analysis
• Ability to work with large and complex data sets.
• Experience with programming (e.g., Python, Shell Script, SQL), data modeling, and developing features within hyperscaler cloud environments.
• Basic understanding of GitHub.