Data Engineer Azure

Sai Prasad Barkam

Data engineer

+1-334-***-**** *****************@*****.*** United States

OBJECTIVE: Accomplished data professional with 2+ years of experience in various data-centric roles, including data engineering, analysis, and reporting. Expertise in designing, building, and optimizing scalable data pipelines and ETL processes using Azure Data Factory, Databricks, Python, and SQL. Strong background in data transformation, integration, and validation to ensure data accuracy and consistency. Proficient in developing data models and delivering actionable insights through visualization tools. Adept at solving complex data problems and driving data-driven decisions that improve business outcomes. Passionate about leveraging data to enhance processes, improve efficiency, and support strategic decision-making in a fast-paced environment. Seeking to contribute my skills and experience in a dynamic data-focused position.

Technical Skills

Programming Languages:

Python, R

Visualization Tools:

Power BI, Tableau, Lucid Chart, Rapid Miner, MS Office

Operating Systems:

Linux, Windows.

Databases:

Oracle SQL, MySQL, MS Access

Cloud Services:

Azure(Databricks, Data Lake, Blob Storage, Active Directory) AWS(S3, Glue, Lambda, Kinesis)

Software Methodologies:

Agile, SCRUM, SDLC

Warehouses & ETL Tools

Snowflake, Redshift, Synapse Analytics, Azure Data Factory, Informatica, Apache NiFi, Talend

Professional Experience :

Tata Consultancy Service Hyderabad, India

Data Engineer Apr 2023

Developed and optimized complex SQL queries to extract, transform, and load data from Oracle and other relational databases, improving performance and scalability for large data volumes.

Ensured compliance with HIPAA and PII regulations by implementing robust data governance practices, including encryption, anonymization, and secure data storage in Azure environments to protect sensitive healthcare and personal data.

Designed and implemented end-to-end ETL pipelines using Azure Data Factory (ADF) to automate data ingestion, transformation, and loading into Azure Data Lake and Azure Synapse Analytics.

Built scalable data solutions using PySpark for big data processing, transforming raw data into structured formats for analytics and reporting in distributed environments.

Managed data storage and processing workflows in Azure Data Lake, ensuring data security, partitioning, and proper access controls for large datasets.

Wrote Python scripts for data cleaning, transformation, and validation, automating data workflows and improving data quality across different stages of the pipeline.

Worked with Oracle PL/SQL to develop stored procedures, triggers, and functions for complex data operations, ensuring high efficiency and accuracy in data processing.

Developed and maintained Power BI dashboards and reports, integrating data from multiple sources to provide real-time, actionable insights for business stakeholders.

Monitored and optimized data pipelines to ensure minimal latency, high availability, and resilience, leveraging Azure monitoring tools like Azure Monitor and Log Analytics.

Collaborated with cross-functional teams to gather business requirements, translating them into technical specifications and data models that support advanced analytics.

Implemented CI/CD pipelines using Jenkins for automated deployment, testing, and monitoring of data pipelines, reducing manual intervention and increasing the efficiency of deployments in Azure environments.

Ensured data security and compliance by implementing encryption, role-based access controls, and adherence to governance standards such as GDPR in Azure environments.

Cognizant Technology Solutions Hyderabad, India

Data Analyst Jun 2022

Utilized SQL to extract and query retail sales data from relational databases, generating detailed reports and performing complex data manipulations to uncover sales trends and insights.

Developed and maintained interactive dashboards and visualizations using Tableau to track key performance metrics such as sales performance, customer behavior, and inventory levels, enabling data-driven decision-making.

Leveraged Python for data analysis and automation, using libraries like Pandas and NumPy to clean, process, and analyze large datasets, and to build predictive models for sales forecasting and trend analysis.

Created and automated reporting processes to streamline the generation of sales reports, leveraging Python scripts and SQL queries to ensure timely and accurate delivery of insights.

Conducted detailed analysis on sales metrics, including revenue, profit margins, and sales growth, using SQL and Python to provide actionable recommendations for marketing and merchandising strategies.

Collaborated with cross-functional teams to gather business requirements and translate them into technical specifications for data analysis, utilizing Tableau for visualization and reporting.

Performed data cleansing and validation to ensure the accuracy and consistency of sales data, integrating data from various sources including point-of-sale systems and e-commerce platforms.

Monitored and analyzed sales performance metrics to identify opportunities for process improvements, leveraging insights to optimize pricing strategies and promotional campaigns.

Presented findings and insights to stakeholders through clear and compelling Tableau dashboards and Python-generated reports, facilitating informed decision-making across the organization.

Conducted market and competitor analysis using sales data and Python-based analytical techniques to provide insights into market trends, customer preferences, and competitive positioning.

PROJECTS:

Restaurant Database Management and Analysis

Developed and administered a sophisticated restaurant database, employing advanced SQL techniques to optimize relational schema design and enhance operational efficiency.

Leveraged data visualization tools to generate detailed reports that identified key sales trends and menu performance metrics.

Analyzed complex data sets to drive strategic business decisions, significantly improving resource allocation and marketing strategies.

Streamlined database management processes, leading to a more efficient analysis of customer behavior and revenue generation opportunities.

Payment Method Optimization for Supply Chain Logistics

Served as a strategic consultant to revamp payment methodologies for a prominent supply chain logistics firm, enhancing efficiency through detailed analysis and customized solutions.

Spearheaded the development of strategic recommendations focused on integrating digital payment solutions and refining invoicing processes to streamline financial operations.

Oversaw the implementation of new payment strategies, monitoring their impact on financial performance and customer satisfaction to ensure optimal outcomes.

Contributed to significant improvements in payment efficiency, which increased transaction speed and reduced processing errors, enhancing overall business operations.

EDUCATION

Auburn University at Montgomery Montgomery, AL 36117

Master of Science in Management Information Systems, GPA 3.69 May 2023 - August 2024

Osmania University (OU) Hyderabad, India

Global Institute of Technology, GPA 7.10 July 2018- September 2021

Relevant Coursework: Data Analytics, Database Management, Data Warehousing, Data Visualization, Information Systems, Application Development, Project Management, Information Security Management, and System Analysis Design.

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