Open to opportunities

Atul Anjan

@atulanjan

Message

Data engineer specializing in AWS and Databricks lakehouse pipelines, ETL/ELT, and governed billion-row analytics.

India

Message

What I'm looking for

I’m looking for a Data Engineering role where I can build governed, high-performance cloud-native pipelines—especially Lakehouse ETL/ELT on AWS and Databricks—while improving SLAs, automating deployments/monitoring, and partnering on modern analytics platforms.

I’m a results-driven Data Engineer with 4+ years of experience designing and optimizing scalable cloud-native data platforms using AWS, Databricks, Snowflake, PySpark, SQL, and Python. I focus on building high-performance ETL pipelines and Lakehouse architectures that help organizations modernize data and deliver faster analytics on billion-row datasets.

In my roles, I’ve delivered measurable business impact through performance optimization, cloud migration, automation, and governed enterprise data solutions. I’ve built Databricks Lakehouse pipelines with sub-12 minute SLA, designed event-driven ingestion across Bronze-Silver-Gold using Unity Catalog, and improved reporting performance by 60% while migrating legacy workflows and integrations to native AWS services.

Experience

Work history, roles, and key accomplishments

Current

Data Engineer

Current

Velotio Technologies

Aug 2025 - Present (10 months)

Built and optimized Databricks Lakehouse pipelines processing billions of telecom records with a sub-12 minute SLA using liquid clustering and autoscaling clusters. Designed event-driven S3→Lambda→Databricks ingestion across Bronze-Silver-Gold with Unity Catalog, and automated deployments and monitoring via GitHub CI/CD with alerting.

Databricks AWS S3 AWS Lambda Databricks Workflows Unity Catalog Pyspark Delta Lake AWS Glue CI CD Data Governance

Data Engineer

Principal Global Services

Jul 2022 - Aug 2025 (3 years 1 month)

Architected enterprise data pipelines with AWS, Snowflake, PySpark, and Informatica, improving reporting performance by 60% and accelerating business decision-making. Migrated legacy SSIS to Informatica PowerCenter (95% reduction in batch runtime) and MuleSoft integrations to native AWS services, delivering $1M+ annual cost savings, while implementing governed data access with Lake Formation.

AWS Snowflake Pyspark SQL Informatica SSIS AWS Lambda