Data Engineer Power Bi

ANEESHA PATAN ARIFULLA

USA +1-845-***-**** ************@*****.*** LinkedIn GitHub Portfolio PROFESSIONAL SUMMARY

Data Engineer with 3+ years of experience designing, building, and optimizing Azure- based ETL/ELT pipelines, data warehouses, and big data solutions across healthcare and financial domains. Skilled in Azure Data Factory, Synapse, Databricks, Delta Lake, Python, SQL, and Power BI to deliver high-performance, compliant, and scalable data solutions. Experienced in real-time streaming, pipeline automation, and data governance, ensuring HIPAA and regulatory compliance. Proven ability to create self-service data marts, dashboards, and analytics frameworks that accelerate decision-making and improve operational efficiency. Collaborative and results-driven, focused on enabling actionable insights and business impact.

TECHNICAL SKILLS

Programming & Data Processing: Python, SQL, PySpark, Pandas Azure Ecosystem: Data Factory, Synapse Analytics, Databricks, Fabric, Delta Lake Data Warehousing & ETL: Snowflake, dbt, Apache Airflow Big Data & Streaming: Apache Spark, Kafka

Data Visualization: Power BI, Tableau

Databases: SQL Server, PostgreSQL, MySQL

Governance & Compliance: HIPAA, GDPR, IAM, Data Security & Access Controls Collaboration: JIRA, Confluence, Agile/Scrum

PROFESSIONAL EXPERIENCE

Data Engineer Aug 2024 - Present

Quadrant Technologies United States

• Automated large-scale ETL workflows in Azure Data Factory and Databricks

(PySpark), cutting preparation cycles by 40% and speeding up healthcare analytics.

• Built a compliant data warehouse on Azure Synapse & Fabric, enabling 99.9% accuracy in HIPAA audit reports and supporting population health insights.

• Tuned transformations in Databricks Delta Lake, trimming query runtimes by 45% and allowing analysts to seamlessly scan 500M+ patient records.

• Embedded Great Expectations checks within pipelines, catching anomalies proactively and driving a 30% drop in recurring production data errors.

• Streamed patient vitals in near real time via Azure Event Hubs + Spark, giving clinicians alerts in under 5 seconds to improve critical care response.

• Delivered self-service Synapse data marts and Power BI dashboards, easing dependence on engineering teams and lowering ad-hoc requests by 35%.

• Enforced row-level security, RBAC, and end-to-end encryption in Azure, ensuring zero compliance violations across sensitive health datasets. Data Engineer Oct 2019 - May 2022

Capgemini Pvt. Ltd. India

• Built ETL pipelines with Azure Data Factory, SQL, and Python to process daily financial and transaction feeds, ensuring 10M+ records were consistently available for risk and compliance teams.

• Migrated disparate financial data into an Azure Data Lake, reducing storage costs by 25% while giving analysts unified access to market and payment datasets.

• Restructured Azure Synapse schemas and optimized query performance, which cut reporting time by 30% and delivered faster audit-ready datasets.

• Deployed real-time Spark streaming jobs on Azure Databricks, enabling 20% higher fraud detection accuracy and faster investigator alerts.

• Designed Power BI dashboards for liquidity and risk metrics, which empowered senior managers to accelerate decision-making and shorten reporting cycles by 25%.

• Automated overnight workflows through ADF pipelines and scheduling, eliminating manual intervention and reducing pipeline failures by 50%.

• Applied row-level security, RBAC, and encryption in Azure, maintaining 100% compliance with financial regulations across sensitive datasets.

• Diagnosed recurring failures in ADF and Databricks pipelines, introduced proactive monitoring, and reduced recovery time by 40%, sustaining high data reliability.

PROJECTS

Healthcare Data Lake & Compliance Analytics

• Integrated EHR, lab, claims, and IoT device data from 10+ sources into Azure Data Lake Storage and Synapse, enabling analysts to access unified patient data faster and reducing manual consolidation by 40%.

• Automated ETL pipelines using Azure Data Factory and Python, processing millions of records daily while cutting pipeline runtime by 35%.

• Modeled Synapse and Snowflake schemas for claims and patient outcomes, supporting HIPAA-compliant reporting and enabling Power BI dashboards to reduce claim rejections by 15%.

Financial Data Warehouse & Fraud Analytics

• Consolidated trading and market data into Azure Data Lake and Synapse, allowing analysts to perform multi-source analytics on high-volume financial transactions efficiently.

• Built Spark-based streaming and batch analytics on Azure Databricks to detect anomalies in transactions, improving fraud detection accuracy by 20% while lowering false positives by 18%.

• Developed interactive Power BI dashboards for transaction monitoring, risk metrics, and compliance reports, enabling executives to make timely decisions and reducing reporting turnaround by 25%.

EDUCATION

Master of Science in Computer Science Aug 2022 - Dec 2023 State University of New York New Paltz

Bachelor of Engineering in Computer Science Jun 2015 - Apr 2019 Sri Venkateswara College of Engineering & Technology CERTIFICATIONS

• Azure Databricks & Spark for Data Engineers: Hands-on Project

• Microsoft Certified: Fabric Data Engineer Associate

• Microsoft Fabric: End-to-End Data Engineering Project

• IBM Data Engineering Professional Certificate - Coursera

• Introduction to Data Engineering - Coursera

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