Open to opportunities

Kushal User

@kushaluser3

Senior Data Engineer modernizing lakehouse and streaming data platforms for regulated healthcare, insurance, and finance.

United States

Message

What I'm looking for

I’m looking to build scalable, cost-efficient lakehouse and streaming data platforms for regulated domains—owning ETL/ELT, orchestration, data quality, governance, and observability, and partnering with teams to ship analytics-ready datasets (and AI-ready pipelines).

I’m a Senior Data Engineer with 7+ years of experience designing and modernizing enterprise-scale data platforms across healthcare, insurance, and financial services. I focus on building scalable ETL/ELT pipelines and analytics-ready datasets that teams can trust.

My work centers on Lakehouse and data warehouse architectures, including building governed raw/curated/trusted zones and enabling a “single source of truth” for hospital operations and analytics. I’ve delivered reliable batch and near real-time processing using Python, SQL, Apache Spark (PySpark), Databricks, dbt, and orchestration with Apache Airflow.

I bring strong multi-cloud capabilities across AWS, Azure, and GCP—leveraging S3/GCS, Redshift/Snowflake/BigQuery, Databricks, and messaging/streaming with Kafka, Kinesis, and Pub/Sub. I also prioritize observability and data quality with CloudWatch/Azure Monitor/Datadog and Great Expectations/Deequ, while implementing HIPAA/GDPR-aligned governance via IAM, RBAC, and data cataloging.

I’ve supported AI-focused initiatives too, including building RAG pipelines and vector-based document retrieval using LangChain and Hugging Face, and integrating ML feature/monitoring workflows into production data pipelines.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

HCA HealthCare

May 2024 - Present (2 years 2 months)

Architected an enterprise Lakehouse platform for LifePoint Health, building governed raw/curated/trusted zones and governed single source of truth across clinical and analytics teams. Built scalable batch and near-real-time ETL/ELT pipelines with PySpark on Databricks, AWS Glue/FHIR/HL7 ingestion, Kinesis/Kafka streaming, dbt/SQL transformations, Airflow orchestration, and enterprise monitoring/go

Data Engineer

MetLife

May 2023 - Apr 2024 (11 months)

Developed and optimized scalable enterprise data platforms on GCP using Databricks, Snowflake, and BigQuery for insurance, healthcare, and financial datasets. Built batch and near-real-time ETL/ELT pipelines with PySpark, Dataproc, Dataflow, and Apache Beam; implemented event-driven ingestion with Pub/Sub and Cloud Functions; and supported data governance, CI/CD, and operational monitoring.

GCP BigQuery Dataflow Pub Sub Cloud Functions Databricks Snowflake Pyspark Apache Spark Apache Beam ETL ELT SQL Python IAM Encryption Jenkins Cloud Build Git Jira Agile Scrum HIPAA GDPR

Data Engineer

Visa Inc.

Jun 2021 - Apr 2023 (1 year 10 months)

Designed scalable data ingestion pipelines with Azure Data Factory to load global remittance and customer activity data into Azure Data Lake Storage Gen2 for analytics and compliance reporting. Built distributed transformations with PySpark on Databricks and Snowflake, implemented Delta Lake Lakehouse architecture, orchestrated multi-stage workflows across Synapse/Databricks/Snowflake, and deliver

Big Data Developer

Liberty Mutual

Sep 2018 - May 2021 (2 years 8 months)

Built scalable Hadoop batch data pipelines for insurance claims, policy, and underwriting datasets to support risk modeling and actuarial analytics. Developed ingestion and transformations using Sqoop, Hive, Pig, Oozie, Flume, MapReduce (Java), and improved performance and data quality through Hive partitioning/bucketing, YARN tuning, and optimized storage formats like Avro and Parquet.