Big Data Lead

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. 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. 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