Open to opportunities

PAVANSAI ACHIMSETTY

@pavansaiachimsetty

Message

Data engineer building scalable cloud-native platforms for analytics and AI.

United States

Message

What I'm looking for

I seek a role building scalable, secure cloud data platforms that enable analytics and ML/GenAI, with collaborative teams and opportunities to optimize performance and costs.

I am a data engineer with 5+ years designing and operating cloud-native data platforms across financial and healthcare domains, focused on reliable, secure, and compliant data systems that enable analytics and ML/GenAI use cases.

I have built end-to-end ETL/ELT and near-real-time ingestion pipelines using AWS (Glue, S3, Kinesis, Redshift, Bedrock) and Azure (Data Factory, Synapse, Databricks), improved query and ETL performance, and implemented production controls for data quality, observability, and cost optimization.

I partner closely with data science, product, and business teams to translate requirements into analytics-ready models and feature pipelines, delivering measurable outcomes such as reduced latency, cost savings, and accelerated data-driven decision-making.

Experience

Work history, roles, and key accomplishments

Current

Data Engineer

Current

Fidelity

Jan 2024 - Present (2 years 1 month)

Architected and operated AWS-native ingestion and ETL/ELT pipelines supporting fraud analytics and ML workloads, achieving 99.9% data reliability and accelerating data-driven decision-making by 25%; delivered analytics-ready models that produced $3K weekly cost savings.

AWS Glue S3 Kinesis Apache Spark Data Modeling ETL CI CD Data Quality

Data Engineer

Philips Healthcare

Mar 2019 - Jul 2022 (3 years 4 months)

Built Azure-native analytics platforms and scalable batch pipelines using ADF, Databricks, and Synapse, reducing ETL execution time by 30% and cloud spend by 20–25% while improving data quality incident rates by 30–35%.