Jagadish Tarla

I’m a results-driven Data Engineer with 5 years of experience building scalable data platforms, cloud-native ETL/ELT pipelines, and real-time analytics solutions across enterprise consulting and pharmaceutical environments. I focus on designing high-performance data architectures that produce analytics-ready datasets for BI and machine learning use cases.

Most recently at Boehringer Ingelheim, I design and maintain enterprise-scale pipelines for commercial analytics and operational reporting. I build reusable transformation pipelines and dimensional data models for KPI dashboards, automate data validation and orchestration to reduce manual reporting by ~25%, and implement role-based access control and audit-ready governance for regulated settings.

Previously at Accenture, I architected 15+ production-grade ETL pipelines using Apache Airflow and Apache Spark, processing 50GB+ daily into Snowflake. I delivered real-time event-streaming pipelines with Kafka that reduced reporting latency from T+1 day to under 15 minutes, improved dbt self-service adoption by 40%, optimized SQL/SOQL workloads to cut compute costs by 25%, and automated CI/CD deployments with GitHub Actions while mentoring junior engineers.