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omkarjadhav296

Omkar A. Jadhav

@omkarjadhav296

Geospatial Consultant and Data Engineer

India
Inglés
Parte de la información aparece en idioma inglés.
Sobre mí
I am a results-driven Geospatial Data Engineer with over 4 years of experience designing batch and near real-time data pipelines and cloud-native architectures. I specialize in Python, SQL, and Spark to build scalable data transformations and dimensional models for BI and ML applications. I have a proven track record of meeting SLAs for global clients like the World Bank and ISRO.... Lee más

Habilidades

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omkarjadhav296
Omkar A. Jadhav
desconectado • 
Tiempo medio de respuesta: 1 hora

Revisa mis servicios

Consultoría de ingeniería de datos
I will build automated spatial etl pipelines and data lakes

Experiencia laboral

Upwork

Geospatial Consultant

Upwork • Trabajador autónomo

Jul 2025 - Present1 yr

• Designed and built a cloud-native, modular ETL pipeline in Python to ingest structured data from multiple sources, apply reusable transformation logic, and load outputs into a structured data lake supporting both batch and near real-time ingestion patterns. • Orchestrated end-to-end pipeline scheduling with Apache Airflow DAGs, configuring task-level retries, failure alerting (email/Slack callbacks), SLA breach detection, and dependency management across multi-step ingestion workflows. • Implemented data quality checks at each pipeline stage schema validation, null/duplicate reconciliation, and audit timestamp fields ensuring reliable, auditable data delivery to downstream analytics consumers. Deployed CI/CD (GitHub Actions) for automated pipeline testing.

World_Bank

Senior Research Fellow (RS & GIS)

World Bank • Tiempo completo

Dec 2023 - Jul 20251 yr 7 mos

• Designed and operationalized data ingestion pipelines delivering infrastructure indicators to a central data warehouse, supporting World Bank reporting SLAs and full audit requirements. • Led technical capacity-building workshops for the Central Water Commission (Govt. of India) and World Bank on ET-based irrigation assessment tools. • Automated validation workflows using PyQGIS to verify third-party hydrological data accuracy, ensuring robust model inputs. • Optimized Machine Learning models for facility planning, utilizing spatial factors to predict optimal resource allocation.