Data Engineer Enterprise

Aravind Badepally Data Engineer

NY, USA +1-551-***-**** *******.***********@*****.*** LinkedIn SUMMARY

Data Engineer with 4+ years of experience delivering measurable impact across finance and healthcare organizations. Improved fraud detection speed by 50%, cut reporting cycles from 24 hours to 6 hours, and enhanced pipeline reliability by 35%. Skilled at transforming complex data into accurate, audit-ready insights that support compliance, reduce costs, and accelerate decision-making for business leaders. Proven track record of driving efficiency and reliability in enterprise data environments. TECHNICAL SKILLS

Data Engineering & Pipelines: ETL/ELT Development, Airflow, Spark, Kafka, Databricks, Real-Time Processing, Batch Processing, Data Validation, Data Lineage

Databases & Cloud: Snowflake, AWS S3, Azure Data Lake, Oracle, SQL Server, PostgreSQL, Cloud Migration Big Data & Analytics: PySpark, Distributed Processing, Financial Data Integration, Healthcare Data (HL7, FHIR, Claims), Anomaly Detection, Predictive Modeling Pipelines

Compliance & Governance: Basel III, GDPR, HIPAA, HITRUST, Metadata Management, Audit Controls, Regulatory Reporting Optimization & Automation: Workflow Automation, Pipeline Monitoring, Alerting & Recovery, Infrastructure Cost Reduction, Performance Tuning, Scalable Data Pipelines

Collaboration & Delivery: Cross-Functional Collaboration (Risk, Compliance, Analytics, Clinical Teams), Executive Reporting, Dashboard Enablement, Enterprise Data Strategy Alignment

PROFESSIONAL EXPERIENCE

Capital One, NY, USA Jan 2025 - Current

Data Engineer

• Reduced fraud detection latency 50% by engineering Spark and Kafka pipelines supporting real-time transaction monitoring across millions of daily events.

• Shortened batch processing cycles 40% by automating ingestion of JSON, Parquet, and CSV datasets into Snowflake and S3 environments.

• Improved compliance reporting accuracy 25% by deploying data lineage and validation frameworks across enterprise-scale financial systems.

• Lowered infrastructure spend 18% by optimizing Snowflake storage structures and AWS resource utilization for large-scale analytics workloads.

• Accelerated risk model execution 30% by restructuring ETL workflows, reducing execution bottlenecks, and enhancing orchestration efficiency.

• Enabled faster regulatory filings by integrating audit-ready datasets, cutting reporting turnaround time from 7 days to 3 days. Citigroup Inc., India Nov 2021 - Jul 2023

Data Engineer

• Cut financial reporting latency from 24 hours to 6 hours by building Airflow-driven ETL pipelines integrating multi-source transaction and CRM data.

• Reduced regulatory risk by ensuring 100% Basel III and GDPR compliance through automated metadata tagging and audit controls.

• Improved portfolio risk visibility 35% by curating data marts powering executive dashboards for credit exposure and treasury reporting.

• Migrated 60+ legacy workflows into cloud pipelines, improving scalability and cutting downtime 40% during peak processing periods.

• Enhanced anomaly detection accuracy 20% by embedding machine-learning-based validation checks into production financial data pipelines.

• Strengthened global finance operations by delivering high-quality, secure datasets used by 400+ analysts across multiple regions. Citius Tech, India Nov 2019 - Oct 2021

Data Engineer

• Delivered healthcare pipelines processing HL7, FHIR, and claims datasets, reducing payer analytics turnaround 30% across enterprise clients.

• Increased pipeline reliability 35% by implementing automated monitoring, alerting, and recovery workflows in production environments.

• Improved patient care strategies by operationalizing readmission risk models, achieving 22% better accuracy in clinical predictions.

• Secured sensitive datasets with HIPAA-compliant ETL solutions, reducing audit findings by 100% during annual compliance checks.

• Lowered infrastructure costs 15% by migrating workloads to Azure Data Lake and Databricks platforms.

• Enhanced reporting accuracy for provider clients by integrating validation layers, cutting manual reconciliation efforts 40%. EDUCATION

Master of Science in Business Analytics May 2025

St. Francis College, NY, USA

Bachelor of Technology in Electrical and Electronics Engineering Jul 2021 Vardhaman college of engineering, India

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