Nitish Songara

I'm a freelance Data Engineer with 4+ years of professional experience building enterprise-grade data pipelines and cloud infrastructure at Deloitte and Ascendeum. I specialize in delivering scalable ETL/ELT solutions, database optimization, and business intelligence systems—all remotely with measurable results.

Professional Background:

Ascendeum (June 2025 – Present) | Associate Data Engineer

Currently working remotely, I automate ETL pipelines that process 500M+ events monthly from AWS S3 into MongoDB, powering analytics dashboards for 50+ stakeholders. I've improved MongoDB performance by 60% through strategic indexing and sharding, reducing dashboard latency from 30 seconds to under 10 seconds. I migrated legacy Pandas workflows to PySpark, achieving 5x performance improvements on 200GB+ daily datasets. My work includes deriving KPIs from raw event data and collaborating with business teams to design data-driven strategies that increased client ROI by 12-15%.

Deloitte (August 2021 – May 2025) | Data Engineer

Spent nearly 4 years in Bengaluru designing and maintaining Azure Data Factory and Databricks pipelines processing 20M+ records weekly (~1TB monthly) from 10+ sources. I built modular PySpark and SQL frameworks that cut pipeline development time by 30%. I developed SQL models and optimized views serving 200+ business users, improving query performance by 40% and saving 300+ engineering hours annually. Implemented SQL Server optimization routines that reduced reporting query times by 20-25%. Enhanced pipeline reliability to 99.9% uptime through automated data quality checks, proactive monitoring, and schema evolution handling.

Services I Offer as a Freelancer:

ETL/ELT Pipeline Development: Python, PySpark, Apache Airflow workflows for batch and real-time processing

Cloud Infrastructure: AWS S3, Azure Data Factory, Databricks optimization and implementation

Database Management: MongoDB, SQL Server performance tuning, indexing, sharding, query optimization

Business Intelligence: Power BI dashboard development, KPI derivation, data modeling

Data Quality & Monitoring: Automated validation frameworks, error handling, pipeline reliability

Technical Skills: Python, SQL, PySpark, Databricks, MongoDB, Azure Data Factory, AWS, Power BI, Delta Lake, ETL/ELT, Data Modeling

Certifications: Microsoft Certified DP-203 (Azure Data Engineer Associate), DP-300 (Database Administrator Associate), AZ-900 (Azure Fundamentals)