
Bhargavi Marri
Data engineer II
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About
Data Engineer with 4+ years of experience building scalable data platforms using Palantir Foundry, Microsoft Azure, and Databricks. Proficient in designing end-to-end data pipelines in Palantir Foundry using Contour, Pipeline Builder, and Code Repositories (Transforms) for enterprise-grade data integration and analytics. Experienced in Azure Data Factory, Azure Databricks, Azure Data Lake, SQL, Python, Logic Apps, Azure Functions, and Service Bus messaging.
Skilled in building ETL/ELT pipelines, healthcare data platforms, and modern data lake architectures using the Medallion architecture pattern (Landing/Bronze/Silver/Gold). Adept at leveraging Palantir's ontology-driven approach to connect raw data to real-world business objects for operational decision-making. Familiar with Generative AI integrations for intelligent data workflows.
Experience
Data Engineer II at Fifthnote | Ensemble Health Partners (2024-08 – Present)
- Designed and developed scalable ETL/ELT pipelines using Azure Data Factory, Azure Databricks, and Palantir Foundry to ingest and transform healthcare data from multiple operational systems.
- Built and managed data pipelines in Palantir Foundry Code Repositories (Transforms) using Python, implementing modular transformation logic for healthcare datasets.
- Leveraged Palantir Pipeline Builder for no-code/low-code pipeline orchestration, enabling rapid development and iteration of data workflows.
- Utilized Palantir Contour and Quiver for exploratory data analysis and interactive dashboards, empowering business stakeholders with self-service analytics.
- Configured Foundry Ontology objects to model real-world healthcare entities (patients, claims, encounters), enabling operational applications via Workshop.
- Implemented modern Azure Data Lake architecture following the Medallion architecture (Landing → Bronze → Silver → Gold) for structured data processing.
- Built automated ingestion pipelines in Azure Data Factory and Palantir Data Connection to load data from APIs, databases, and flat files.
- Developed transformation pipelines in Azure Databricks (PySpark) and Foundry Transforms to cleanse, standardize, and enrich healthcare datasets.
- Implemented incremental data processing and event-driven ingestion using Azure Service Bus and Foundry webhook-based triggers.
- Developed serverless automation using Azure Function Apps, Logic Apps, and Foundry Actions for workflow orchestration and monitoring.
- Managed data lineage, access controls, and pipeline health monitoring using Foundry's governance tools (Monocle, Health Checks).
Data Engineer at Luminaire Technologies Limited (2022-06 – 2024-07)
- Developed and maintained enterprise data pipelines on Palantir Foundry for healthcare clients, enabling data-driven decision-making across clinical and operational workflows.
- Built data transformation logic in Foundry Code Repositories (Transforms) using Python and PySpark to process large-scale patient, provider, and claims datasets.
- Designed and configured Ontology objects for healthcare entities (patients, providers, procedures, insurance plans), enabling downstream operational applications.
- Created interactive dashboards using Palantir Contour and Quiver for clinical operations, utilization review, and financial reporting.
- Built Workshop applications for care management teams to track patient journeys, flag high-risk encounters, and streamline prior authorization workflows.
- Configured Palantir Data Connection to ingest data from EHR systems, third-party APIs, SFTP feeds, and relational databases into Foundry.
- Implemented Pipeline Builder schedules and dependency chains for complex multi-step data processing with automated error handling.
- Developed Azure Data Factory pipelines for batch ingestion and Azure Databricks notebooks for data cleansing and enrichment of clinical datasets.
- Managed data quality checks, lineage tracking, and access controls using Foundry governance tools to maintain HIPAA compliance.
Education
Bachelor of Computer Science in Computer Science – Sri Padmavati Womens Degree College, Tirupati (2019 – 2022)