Open to opportunities

Samip Sedhain

@samipsedhain

Message

I am a Senior Data Engineer specializing in cloud-native, scalable ETL, data warehousing, and real-time analytics.

United States

Message

What I'm looking for

I seek cloud-native data engineering roles where I can build scalable ETL and real-time pipelines, drive data governance and ML productionization, work in collaborative Agile teams, and deliver measurable cost and performance improvements.

I am a Senior Data Engineer with over 6 years of experience designing and implementing scalable data solutions across AWS, Google Cloud, and Microsoft Azure, specializing in end-to-end analytics, ETL pipelines, data lakes, and data warehouses. I have reduced cloud expenses by 15-20%, improved processing times by up to 60%, and ensured HIPAA and GDPR compliance in healthcare and financial environments.

I build event-driven real-time and batch pipelines using Apache Airflow, Kafka, AWS Glue, Spark, dbt, and Snowflake, and automate CI/CD with Terraform, Docker, Kubernetes, and GitHub Actions to accelerate deployments. I collaborate with data scientists to productionize ML workflows, mentor junior engineers, maintain strong data governance, and drive actionable analytics for business impact.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

Signify Health

Dec 2022 - Present (2 years 8 months)

Developed and optimized ETL and real-time pipelines using AWS Glue, Python, Airflow, and Kafka to support behavioral health analytics, improving data accuracy by 40% and reducing processing time by 60%. Implemented data governance and HIPAA/GDPR controls and reduced cloud costs by 15% through query optimization and autoscaling.

AWS Glue Python Snowflake Apache Airflow Apache Kafka DBT Terraform Apache Spark AWS S3

Data Engineer

Charles Schwab

Feb 2020 - Nov 2022 (2 years 9 months)

Built and optimized multi-cloud ETL pipelines with Apache Spark, Azure Data Factory, and Google Cloud Dataflow, reducing data processing time by 35% and improving pipeline reliability by 40%. Led data warehouse and lake migrations to BigQuery, Synapse, and Redshift, improving reporting speed by 25% and mentoring junior engineers.

Apache Spark Azure Data Factory Google Cloud Dataflow BigQuery Databricks Apache Kafka Apache Airflow DBT Terraform

AWS Data Engineer

Nationwide

Dec 2018 - Jan 2020 (1 year 1 month)

Designed ETL workflows using AWS Glue, Apache Spark, and Python to optimize claims and underwriting data processing, improving speed by 30% and enabling real-time reporting via Redshift with 25% faster retrieval. Migrated legacy systems to cloud and enforced IAM/KMS security controls, reducing maintenance costs by 20%.