AWS Glue & Spark Expert | Scalable ETL | MongoDB | Data Pipelines

Bangalore, India

Only remote

B.Tech in Computer Science

Bangalore, India

Only remote

B.Tech in Computer Science

Profile attachments

Application Programming Interfaces (APIs)AdvertisingApache AirflowAmazon Web ServicesAmazon S3Data ValidationData DeduplicationExtract Transform Load (ETL)DebuggingGoogle AdSensePython (Programming Language)MongoDBNormalization ProcessesPerformance TuningSQL Databases

Hi, I'm Veerendra — a Data Engineer with hands-on experience building scalable, production-grade ETL pipelines for multi-tenant platforms. I specialize in:

Designing and optimizing AWS Glue + PySpark pipelines
Ingesting data from multiple sources (Meta Ads, Google Ads, APIs, S3)
Cleaning, transforming, and loading into MongoDB, S3, or RDS
Handling per-tenant logic, schema normalization, deduplication
Implementing retry-safe pipelines, data validation, and schema drift handling
Debugging, performance tuning, and cost optimization for AWS jobs

I’ve built and managed pipelines processing large volumes of advertising data across multiple clients at a fast-paced startup — and I know what it takes to move fast without breaking data.
Let’s work together if you need:

ETL development from scratch using AWS Glue/Spark
Fixing or optimizing your existing data pipelines
Setting up schema-aware, tenant-isolated processing systems
Debugging AWS Glue errors and improving job reliability

Tech Stack:
AWS Glue, PySpark, MongoDB, Athena, Step Functions, S3, Airflow, SQL, Python, REST APIs
Let’s connect and get your data flowing — reliably and at scale.

Experience

Professional experience0 - 5 years

Freelancer since2022

Languages

EnglishFluentHindiGoodTeluguNative speaker

Project history

Data Engineer

Innovatily

Other

10-50 team member

Built and maintained robust, scalable ETL/ELT pipelines using Airflow, Python, and AWS Glue to support centralized data environments.
Integrated and transformed data from sources including advertising APIs, S3, and PostgreSQL into AWS Redshift and MongoDB.
Designed and managed relational and dimensional schemas for reporting layers used by business and product teams.
Implemented CI/CD workflows with Jenkins and Docker for automated data job deployment.
Created reports and dashboards in Power BI to support operational and strategic decision-making.
Collaborated with cross-functional teams using agile methodology to gather data requirements and deploy features to production.

Data Engineering Intern

TechNova Analytics

Developed SQL scripts and Python utilities for processing marketing datasets, automated ETL workflows, and documented data mapping logic to improve reporting pipelines.

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