Data Engineer Power Bi

BHAVISHYA PUTTAGUNTA

•github.com/BhavishyaPuttagunta • *******************@*****.*** •LinkedIn:bhavishya-puttagunta Results-driven Data Engineer and Analyst with over 4 years of experience delivering impactful data solutions at scale.Specializing in data analytics, machine learning, and data quality management. Proven expertise in Python, SQL, Power BI, and data governance tools like Ataccama,collibra with a strong track record of improving operational efficiency and decision-making. Seeking opportunities to leverage technical skills and business acumen to extract actionable insights and drive innovation. Technical Skills

● Programming Languages: Python, R, C, SAS,SQL,Java,JQuery

● Data Governance Tools:Ataccama One,Trilium DQ,collibra

● Data Visualization: Power BI, Tableau, Excel

● Cloud Platforms: AWS (Certified Cloud Practitioner), Azure

● Databases: MySQL, PostgreSQL, NoSQL (MongoDB)

● Soft Skills:Strong verbal and written communication,Stakeholder collaboration and alignment,Problem-solving

● Certifications:AWS Certified Cloud Practitioner,Microsoft Certified Power BI Associate,Azure Databricks Engineer,Pega Certified Senior System Architect.

PROFESSIONAL EXPERIENCE:

Data Engineer :Princeton IT Services 09/2024 - Present Client:New York Power Authority

● Designed and implemented scalable ETL processes, enhancing data flow principles aligning with business needs.

● Successfully installed, configured, and implemented the Ataccama One DQ Suite, ensuring 100% alignment with architecture defined by the Solution Engineering team.

● Optimized data governance processes for Financial Management, Procurement, Supply Chain, and Asset Management in SAP ERP, reducing data-related downtime by 15%.

● Assessed and migrated over 500 data quality business rules from Trillium DQ to Ataccama, achieving a 20% efficiency increase.

● Onboarded modules to Ataccama, improving data quality scores for Microsoft Dynamics 365 CRM datasets by 25% and achieving 95% platform adoption with cross-functional teams.

● Enhanced data governance through Ataccama One, leading to a 20% governance efficiency increase.

● Designed a dashboard using Tableau like data visualization technology. Architectured, implemented and deployed new data models and data processes in production.Performed data analysis to generate business insights and managed data warehouse plans for a group of Meta products. The load time of a dashboard was increased from 45.8s to 4.5s. Client: Princeton IT Services (Internal Project) 05/2024 - 09/2024

● Developed a security tool to check and validate existing DNS Records for DMARC, DKIM and SPF Records.

● Implemented a user-friendly DNS Records Generation tool utilizing the Cryptography library in Python.

● Deployed the application using AWS Lambda to a domain owned by Princeton IT Services. Azure Data Engineer:Imbuesys Inc 05/2023 - 05/2024

● Designed and maintained an efficient data pipeline architecture, improving data processing speed by 30% and supporting data-driven decision-making.Developed optimized SQL queries, reducing query execution time by 40% and improving database performance.

● Built and maintained over 15+ interactive dashboards and reports using Power BI and Tableau, enhancing business insights and operational efficiency.Collaborated with cross-functional teams to enhance system functionality, leading to a 25% increase in data accessibility and usability.Designed and implemented ETL pipelines processing millions of records daily, reducing data transformation time by 50%.Effectively communicated insights and recommendations to technical and business stakeholders, influencing strategic decisions and driving a 20% improvement in operational performance.

● Utilized AWS services (CloudFormation, EC2, IAM, Lambda) to deploy scalable solutions, reducing cloud costs by 15%.

● Managed Git repositories, ensuring version control and seamless collaboration across teams, reducing deployment errors by 30%.Leveraged Python for automation, cutting manual data processing efforts by 50% and improving workflow efficiency.

● Developed ETL infrastructure, optimizing data extraction, transformation, and loading, reducing latency by 40% and ensuring real-time data availability.

Client:National Council of State Boards of Nursing

● Designed and maintained a real-time data pipeline on Azure using Event Hubs, Stream Analytics, and Data Factory, improving data processing efficiency by 70% and handling 1,000+ events/sec.

● Processed and transformed real-time and historical stock data with Azure Databricks (PySpark), cutting processing time by 40% and improving query performance by 5x using Azure Synapse Analytics.

● Stored terabytes of structured and unstructured data in Azure Data Lake Storage and optimized querying to reduce retrieval time by 50%.Developed interactive Power BI dashboards for real-time stock tracking and trends, enhancing reporting efficiency by 50%, and automated alerts using Azure Functions to reduce manual monitoring by 90%.

● Leveraged serverless Azure SQL and autoscaling Databricks clusters, reducing cloud costs by 30%, and streamlined automation with ADF triggers to eliminate manual data pipeline interventions.

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