Tejaswani

Data Engineer with 4+ years of experience designing, building, and scaling end-to-end data pipelines and analytics platforms across cloud environments. Strong expertise in Python, SQL, Snowflake, dbt, and Airflow, with a proven track record of delivering reliable ELT workflows and analytics-ready datasets that support executive reporting and business decision-making. Experienced in data modeling, pipeline orchestration, and data quality frameworks, ensuring performance, scalability, and governance across production systems. Known for collaborating closely with analytics, product, and business teams to translate complex requirements into robust data solutions, while supporting experimentation, GenAl-enabled analytics, and enterprise-scale insights. Beyond core pipeline development, I bring a strong focus on data reliability, governance, and long-term maintainability of production systems. I have hands-on experience implementing data validation checks, monitoring frameworks, and reusable transformation layers that improve trust in data and reduce downstream issues. I work closely with analytics, product, and engineering teams to align data models with real business use cases, support experimentation and GenAl-enabled analytics, and ensure data platforms scale effectively as requirements evolve.