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Deepak Anumala

@deepakanumala

Data Engineer focused on scalable ETL/ELT, streaming integrations, and sub-10-minute Spark pipelines on AWS and Databricks.

India

Message

What I'm looking for

I’m looking for a role where I can own scalable ETL/ELT and streaming pipelines—optimizing PySpark on Databricks/AWS, enforcing schema validation, and automating end-to-end delivery to power reliable BI and analytics.

I’m a Data Engineer with 2+ years of production experience designing scalable ETL/ELT pipelines, data warehousing solutions, and real-time streaming integrations. I build PySpark/Databricks workflows that process 2B+ records using strong data modeling, data validation, and Spark performance optimization.

In my current role at Modak Analytics, I integrate SnapLogic, Apache Kafka, AWS Lambda, and AWS S3 to automate ingestion and data reconciliation with execution under 10 minutes per run. I also orchestrate end-to-end delivery using Apache Airflow and schema checks—running every 15 minutes for near real-time ingestion and dependable downstream BI dashboards.

Experience

Work history, roles, and key accomplishments

Current

Data Engineer

Current

Modak Analytics

May 2024 - Present (2 years 1 month)

Designed and implemented scalable PySpark workflows on Databricks, integrating SnapLogic, Apache Kafka, AWS Lambda, and AWS S3 to process and transform 2B+ records across enterprise datasets. Built automated ETL/ELT pipelines scheduled every 15 minutes with schema validation and data quality checks, achieving sub-10-minute runs and reliable API-driven delivery of 200–800+ records per batch to down