Anyutha Reddy
Professional Summary
Data Engineer with 5+ years of experience designing and implementing distributed data systems and production-grade ETL/ELT pipelines using cloud-native data platforms and modern orchestration frameworks. Skilled in Python, SQL, PySpark, Snowflake, Databricks and dbt; experienced delivering compliant analytics for finance, healthcare, and insurance domains.
Technical Skills
Work Experience
- Designed and implemented end-to-end ETL/ELT pipelines in Snowflake and Databricks to process multi-terabyte loan and credit transaction datasets, enabling timely risk reporting and regulatory analytics.
- Built dbt models and standardized transformation layers to produce analytics-ready financial datasets supporting BCBS239 and CCAR compliance frameworks.
- Automated Airflow DAGs to ingest data from internal APIs, AWS S3, and Kafka streams for near-real-time refresh and consistent downstream availability for analytics users.
- Optimized Snowflake performance using materialized views, clustering keys and warehouse sizing to improve query responsiveness for risk and compliance reporting.
- Implemented Infrastructure-as-Code with Terraform to automate Snowflake role provisioning, warehouse scaling and secure environment setup, reducing manual setup time and configuration drift.
- Established PII masking and role-based access control while integrating Datadog and CloudWatch monitoring with alerting to ensure pipeline reliability and audit readiness.
- Designed and maintained ingestion pipelines for EHR, patient encounter and clinical systems using Azure Databricks and Synapse to centralize clinical and operational data.
- Built PySpark and Azure Data Factory pipelines to ingest HL7 and FHIR-formatted healthcare data, delivering timely datasets for operational reporting and clinical analytics.
- Implemented dbt transformation models for claims, patient demographics and billing analytics, enabling consistent schemas for downstream reporting and analytics consumption.
- Collaborated with data governance and security teams to implement HIPAA-compliant PHI masking and integrated Azure Key Vault for secure credential management.
- Implemented data lineage and metadata tracking using Azure Purview to support audit readiness and traceability for clinical and billing datasets.
- Led migration of on-premises SQL Server data warehouse to Azure Synapse preserving schema and history; tuned performance via partitioning, caching and delta optimizations.
- Designed end-to-end data pipelines and curated Snowflake schemas to support claims, policy and customer analytics using AWS-hosted ingestion and Snowflake transformations.
- Ingested raw data from Salesforce, Guidewire and third-party APIs into standardized schemas and built dbt models for underwriting risk assessment and loss analytics.
- Developed reusable Python frameworks for data validation, logging and error handling; integrated Airflow for scheduling, dependency management and monitoring.
- Partnered with actuarial and analytics teams to provide clean, reconciled datasets enabling advanced modeling and pricing simulations.
- Implemented CI/CD pipelines with GitHub Actions and Terraform to automate deployment of dbt models, Airflow DAGs and infrastructure provisioning.
- Tuned Snowflake via clustering, virtual warehouse configuration and query tuning; developed automated reconciliation and backup scripts to support regulatory reporting.
Education
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