Big Data Principal

Key Responsibilities Define analytics strategy, KPI frameworks, and data product standards across teams. Own the enterprise semantic/reporting layer strategy across QuickSight/Tableau and Redshift/Athena. Partner with data engineering and architecture on domain models, data contracts, and self-serve analytics capabilities. Establish and enforce data quality, documentation, and review processes; own escalation and resolution paths for analytics issues. Lead and mentor analysts; manage capacity, prioritization, and quality across multiple workstreams. Communicate insights and trade-offs to executives; drive decision-making with clear narratives and measurable outcomes. Optimize cost and performance of analytical workloads; recommend storage/query patterns (e.g., Redshift vs. Athena vs. row-level caching). Ensure compliance with data governance, privacy, and security standards; steward access policies in coordination with platform teams. Must-Have Skills Leadership of analytics programs and teams; proven stakeholder and executive communication. Mastery of SQL and performance engineering on Redshift; deep Athena/S3 expertise (partitioning, Parquet/ORC, Glue cataloging). Expert BI architecture and governance in QuickSight/Tableau, including semantic layers and certification processes. Advanced Python for analytics automation, reproducibility, and standards. Deep understanding of dimensional modeling, domain-driven design for analytics, and metric governance. Strong grounding in data quality frameworks, documentation practices, and analytics SDLC (versioning, review, release). Nice-to-Have Experience influencing data platform architecture decisions; familiarity with Redshift Spectrum, RA3 architecture, concurrency scaling. Exposure to cost optimization and workload management at scale; capacity planning and SLA definition. Good understanding of using AI tools like Github Copilot or similar for code productivity Fannie Mae experience would be a great advantage