Sr. Data Analyst - Atlanta, GA - Fulltime

Role Summary

We are looking for a Senior Data Analyst to lead complex analyses, define metric frameworks, and elevate analytics standards across AWS data platforms. You will own high-impact dashboards, mentor analysts, and partner with engineering to ensure reliable, performant analytical data.

Key Responsibilities

• Lead design and governance of core KPIs, metric definitions, and semantic layers.
• Deliver complex analytical work using advanced SQL, including performance tuning on RDS/Oracle/Redshift and cost-conscious querying in Athena.
• Use Python to create reproducible analysis (pandas, statsmodels/scikit-learn light use), automation scripts, and data validation checks.
• Define data quality expectations; implement automated checks and anomaly detection; triage and drive resolution with engineering.
• Conduct deep-dive analyses, cohorting, funneling, forecasting, and experiment design.
• Create and maintain STTM Mapping document by coordinating with upstream/downstream stakeholders
• Improve query performance with sort keys, distribution keys, partitioning, predicate pushdown, and compression awareness.
• Establish version control and peer-review processes for analytics assets; contribute to lightweight CI for SQL/tests.
• Mentor analysts; review artefacts for accuracy, clarity, and business relevance.
• Partner with data engineers and product teams on data contracts, schema evolution, and roadmap priorities.

Must-Have Skills

• Expert SQL on RDS/Oracle/Redshift (query tuning, vacuum/analyze awareness) and Athena (partitions, file formats, cost control).
• Advanced BI development and data storytelling; strong UX best practices for dashboards.
• Python for analysis and automation; packaging and reusability of common analytics functions.
• Solid statistics for inference and experiment design; practical application in business contexts.
• Deep understanding of data modeling, dimensional design, and semantic layers.
• Collaboration tools (Confluence/Jira), stakeholder management, and ability to translate business needs into robust analytical solutions.

Nice-to-Have

• Experience with modeling tools; governance of analytics layers.
• Familiarity with AWS Glue Data Catalog, IAM basics for data access, and S3 file formats (Parquet/ORC).
• Exposure to event-based data (Kinesis/SNS/SQS) and data freshness SLAs.
• Build scalable, reusable dashboards and data models in QuickSight/Tableau; enforce consistency and naming standards.
• Good understanding of using AI tools like Github Copilot or similar for code productivity
• Familiarity with Secondary mortgage industry is preferred.