Build, deploy, and support production-grade data pipelines and platforms for structured and semi-structured datasets. Develop Snowflake data models and advanced SQL ELT transformations, implement workflow orchestration and data-quality controls, and improve reliability, observability, lineage, and performance. Partner with product teams and data specialists, troubleshoot production issues, modernize legacy pipelines, and deliver maintainable solutions using Python and cloud technologies.

Builds and maintains enterprise data platform frameworks, including automated pipelines, ingestion, processing, orchestration, data quality, testing, and performance improvements. The role uses Python, SQL, Airflow, Snowflake, dbt, Azure, and streaming technologies. Responsibilities include collaborating with stakeholders across the SDLC, supporting platform users, conducting root cause analysis, providing L2/L3 support, contributing to complex system design, and ensuring scalable, reliable production operations.

Build and maintain analytics-ready datasets, data transformations, semantic models, dashboards, reports, and standardized metrics. Support third-party data integration, AI-enabled analytics, data quality, governance, validation, and ad hoc analysis. Translate business reporting needs into technical requirements and collaborate with analytics engineers, business users, and distributed development teams across investment, risk, operations, finance, and investor relations functions.