AVINASH

Data Analyst Engineer ad4piu@r.postjobfree.com 571-***-****

Professional Summary:

oAround 8 years of professional experience with a proven expertise in cloud technologies such as Azure and AWS, specializing in designing and implementing data pipelines, data storage solutions, and data warehousing systems, while also excelling in real-time data processing, big data platforms, and business intelligence data architecture.

oMy proficiency extends to real-time data processing, big data platforms, and business intelligence data architecture. I possess strong Python development skills, specifically tailored to aid in the development of bridge management programs. Additionally, I excel in visualizing data using Power BI, customizing templates, and reports to meet specific client requirements.

oCreated visually appealing and informative dashboards, reports, and interactive visualizations in Power BI to analyze client required-related data.

oDemonstrated proficiency in analyzing data models, designing databases, and employing data mining and segmentation techniques.

oExtensive experience with reporting packages and databases, including SQL, ensuring efficient data retrieval and manipulation.

oSkilled in programming languages such as Python and R, enhancing capabilities in data analysis and processing.

oDemonstrated proficiency in SQL query formulation, optimization, and database management tasks, ensuring efficient data retrieval and manipulation in Azure SQL Data Warehouse and other databases.

oAdvanced proficiency in Microsoft Office, particularly Microsoft Excel, for comprehensive data analysis and visualization.

oUtilized cutting-edge data analytics techniques, including web analytics, to analyze customer financial and personal data for eligibility determination.

oApplied advanced analytics techniques, including A/B testing to analyze customer eligibility and optimize bridge management operations.

oDeveloped and executed Snowflake SQL queries to transform and manipulate data within the Snowflake Data Warehouse.

oUtilized Cognos v.8.4 for report generation and analysis, leveraging Query Studio and Reports Studio functionalities to extract insights from complex datasets.

oExpertise in creating data pipelines for batch processing, micro-batch streaming, and continuous streaming using Databricks and Azure Data Factory.

oProven track record of leveraging Python libraries such as Pandas, NumPy, and SciPy for efficient data processing and analysis.

oImplemented Google BigQuery for real-time data processing and analytics, enabling the client to gain actionable insights from large-scale datasets efficiently.

oIn-depth understanding and hands-on experience with NoSQL databases like CosmosDB, enhancing capabilities in managing diverse data sources.

oLed data modeling initiatives, designing conceptual, logical, and physical data models for high-volume datasets from various sources like Oracle, Teradata, and SQL Server, ensuring data integrity and optimization.

oDeveloped Python scripts and applications to automate tasks related to transaction activity data, demonstrating strong development skills to enhance data processing efficiency.

oExperience in performing Data Modelling by designing Conceptual, Logical data models and translating them to Physical data models for high volume datasets from various sources like Oracle, Teradata, Vertica, and SQL Server by using Erwin tool.

oExpert knowledge and experience in Business Intelligence Data Architecture, Data Management and Modeling to integrate multiple, complex data sources that are transactional and non-transactional, structured, and unstructured.

oAlso, design and develop relational databases for collecting and storing data and build and design data input and data collection mechanisms.

oPossess good knowledge of MS Dynamics ERP functional flows, particularly Procure to Pay and Order to Cash cycles, with experience in supply chain and inventory management.

Technical Skills:

Cloud Platform

ADFv2, BLOB Storage, ADLS2, Azure SQL DB, SQL server, Azure Synapse, Azure Analytic Services, Data bricks, Mapping Dataflow (MDF), Azure Cosmos DB, Azure Stream Analytics, Azure Event Hub, Azure Machine Learning, App Services, Logic Apps, Event Grid,, Azure Key Vault, Azure Storage Account, Azure DevOps (for CI/CD pipelines, Google Big Query Service Bus, Azure DevOps, GIT Repository Management, ARM Templates, Data Studio

Reporting and BI Tools

Power BI, Tableau, Tableau Prep and Cognos

ETL Tools:

ADFV2, Informatica Power Center 10.x/9.x, DataStage 11.x/9.x, SSIS

Programming Languages & Analysis

PySpark, Python, U-SQL, T-SQL, LINUX Shell Scripting, AZURE PowerShell, C#, Java, Microsoft Excel, R, Microsoft Power BI, R

Big data Technologies

Hadoop, HDFS, Hive, Apache Spark, Apache Kafka, Pig, Zookeeper,

Sqoop, Oozie, HBASE, YARN

Databases

Azure SQL Warehouse, Azure SQL DB, Azure Cosmos No SQL DB, Oracle, Microsoft SQL Server

IDE and Tools

Code, Eclipse, NetBeans, SSMS, Maven, SBT, MS-Project, GitHub, Microsoft

Visual Studio

Cloud Stack

AWS, GCP, Azure, Snowflake, GCP

Methodologies

Waterfall, Agile/Scrum, SDLC

Professional Experience:

Client: CVS Health, RI Aug 2022 - present

Role: Azure Data Engineer

Responsibilities:

oCollaborated with Business Analysts and Solution Architects to gather client requirements and translated them into Azure-based design architectures.

oDemonstrated ability to develop Python scripts and Excel macros to efficiently scrape, process, and analyze data.

oCreated Python scripts using libraries such as BeautifulSoup or Scrapy to scrape data from various sources, including websites and APIs, for further analysis.

oDeveloped Excel macros using Visual Basic for Applications (VBA) to automate data processing tasks, such as data cleansing, transformation, and aggregation.

oIntegrated Python scripts and Excel macros to streamline end-to-end data analysis workflows, allowing for seamless data extraction, manipulation, and visualization.

oDesigned and maintained data pipelines using Azure Data Factory, achieving reduction in data processing time.

oDemonstrated strong Python development skills to develop scripts for bridge management programs, aiding in data processing and automation tasks.

oUtilized Power BI for visualizing bridge-related data, ensuring effective communication with stakeholders by working with current templates.

oIntegrated Google BigQuery into the data processing workflow for handling large datasets and performing advanced analytics.

oImplemented a Power BI integration module for canned reports from ADL

oCollaborated with cross-functional teams and assisted in troubleshooting, risk identification, and resolution.

oDeveloped and executed Snowflake SQL queries to transform and manipulate data within the Snowflake Data Warehouse.

oCollaborated with cross-functional teams to gather data requirements and streamline data processes, fostering a culture of collaborative data management akin to Smartsheet Datamesh's collaborative data meshing approach..

oCollaborated with stakeholders to gather data requirements and optimize SQL queries, resulting in improvement in query performance.

oImplemented data quality checks and validation procedures to ensure data accuracy.

oManaged database performance through index optimization and maintenance tasks and proficiently used SQL Server Import and Export Data tool.

Environment: Azure Cloud, Azure Data Factory (ADF v2), Azure Data Lake, Blob Storage, SQL Server, Big Query, Windows Remote Desktop, Azure PowerShell, Python, PySpark, Azure Cosmos DB, Azure Stream Analytics, Power BI

Client: Wells Fargo, NC Jan 2021 – Jul 2022

Role: Data Analyst

Responsibilities:

oEnsured Wells Fargo's customer eligibility system complied with Securities and Exchange Commission (SEC) regulations for data collection, storage, and usage within the Azure environment.

oDemonstrated proficiency in analyzing data models, designing databases, and employing data mining and segmentation techniques to ensure compliance with Securities and Exchange Commission (SEC) regulations for data collection, storage, and usage within the Azure environment at Wells Fargo.

oExtensive experience with reporting packages and databases, including SQL, ensuring efficient data retrieval and manipulation within Azure.

oSkilled in programming languages such as Python and R, enhancing capabilities in data analysis and processing for bridge management programs.

oPossess strong analytical skills, adept at collecting, organizing, and accurately analyzing substantial data sets related to customer eligibility and bridge management initiatives.

oProficient in query formulation, report generation, and presenting findings, facilitating effective communication of insights using tools like Azure Power BI and Microsoft Excel.

oLeveraged Snowflake SQL to design and create the data warehouse schema, including tables, views, and stored procedures.

oImplemented best practices for data modeling, including dimensional modeling techniques such as star schemas and snowflake schemas, to optimize query performance and facilitate analytics.

oUtilized cutting-edge data analytics techniques to analyze customers' financial and personal data, revolutionizing the process of determining eligibility for bridge financing through effective visualization of data using Power BI and current templates.

oDesigned and implemented an efficient Extract, Transform, Load (ETL) architecture using Azure services (e.g., Azure Data Factory) for seamless data transfer from source servers to the Data Warehouse, with a focus on bridge management program data.

oApplied knowledge of C# for various development tasks related to bridge management programs and utilized Git for managing the repository.

oDemonstrated experience in Azure DevOps Engineering, ensuring effective and efficient management of the infrastructure supporting bridge management initiatives.

oDeveloped and maintained Azure infrastructure, applying knowledge of Azure services such as Key Vault, Storage Account, and subscription management.

oEstablished a culture of data stewardship, ensuring data usage remained aligned with SEC regulations for customer eligibility and bridge management programs.

oImplemented automated data cleansing and integration processes using Azure services, resulting in improved data quality and efficiency in bridge management operations.

Environment: Azure Data factory, Azure Key Vault, Snowflake, Azure Storage Account, Azure DevOps (for CI/CD pipelines and release management), Azure Databricks, Azure Event Hubs, Azure SQL Datawarehouse, Power BI

Client: Molina Healthcare, CA Jan 2017 – Jul 2019 Data Analyst

Responsibilities:

oConducted in-depth analysis of claims and accompanying documentation to ensure strict adherence to policy compliance standards within the healthcare domain.

oDeveloped a nuanced understanding of claim processing dynamics, encompassing both client and service provider viewpoints, and identified key performance metrics to optimize operational efficiency.

oOrchestrated policy servicing and maintenance operations, overseeing tasks such as coverage adjustments, beneficiary data updates, and premium payment processing to uphold seamless policy administration.

oDemonstrated expertise in processing claims data, leveraging insights from Electronic Health Record (EHR) systems and adhering to stringent data privacy and security regulations.

oProficiently extracted data from relational databases and APIs using AWS Glue, seamlessly integrating it into Amazon S3 for streamlined data storage and retrieval.

oEmployed PySpark scripts within the AWS Databricks environment to execute efficient data transformations and conversions, bolstering data analysis capabilities.

oDesigned and implemented data warehousing solutions utilizing AWS Redshift, empowering advanced analysis and insights generation from transformed data sets.

oEngineered Python microservices tailored to healthcare analytics, facilitating seamless integration, and enhancing data processing efficiency.

oMonitored data analytics productivity and resource allocation through AWS CloudWatch Logs, ensuring optimal performance and resource utilization.

oLeveraged AWS Event Hub to capture real-time data streams and funnel them into appropriate data stores, enabling timely analysis and actionable insights.

oVigilantly monitored data pipeline performance using AWS Monitoring and Analytics tools, identifying bottlenecks and optimizing data flow for enhanced analysis.

oPlayed a pivotal role in a comprehensive data migration project involving EHR, ensuring meticulous, accurate, and secure data migration to preserve data integrity and accessibility.

oImplemented data validation checks and constraints using Snowflake SQL to ensure data quality and consistency within the data warehouse.

oDeveloped data cleansing and integration routines in Snowflake SQL to handle data anomalies and discrepancies, improving overall data accuracy and reliability.

oUtilized AWS Kinesis to orchestrate intricate business processes and workflows, facilitating seamless data processing and analysis.

oImplemented serverless computing solutions using AWS Lambda Functions to enhance scalability and cost-effectiveness in data analysis operations.

oDesigned and developed visualization dashboards for comprehensive data analytics leveraging Power BI, enabling stakeholders to derive actionable insights from complex data sets.

oProficiently employed Agile methodology to iterate on data analysis workflows, ensuring adaptability and efficiency in managing project lifecycles and sprints

Environment: AWS Glue, Amazon S3, AWS Redshift, Python, AWS Kinesis, AWS Step Functions, Key Management Service AWS, Log Analytics, Scala, Power BI, Microsoft Excel, R, Microsoft Power BI, Python, R, Snowflake.

Client: Deloitte, Hyderabad May 2015 – Dec 2016

Associate Data Engineer

Responsibilities:

oImplemented data validation, cleansing, and enrichment processes to ensure compliance with regulatory requirements, including SEC and Finra rules.

oDeveloped and automated multiple ETL jobs using Amazon EMR, facilitating seamless data transfer from HDFS to S3.

oCreated batch data pipelines for extracting data from S3 and loading it into RedShift using Glue jobs.

oUtilized PySpark and Scala to automate data ingestion from various sources, including APIs, AWS S3, and Redshift.

oConfigured Spark streaming to store and process real-time data from Kafka.

oLeveraged AWS EMR to store structured data in Hive and unstructured data in HBase.

oCleaned and transformed data in HDFS using MapReduce (YARN) programs for ingestion into Hive schemas.

oDeveloped and maintained data reporting and analytics solutions to support regulatory reporting and compliance monitoring.

oCreated a data lake in Snowflake using Stitch, App Testing, and Production support.

oManaged S3 buckets, implemented policies, and utilized S3 and Glacier for storage and backup on AWS.

oGenerated reports for the BI team by exporting analyzed data to relational databases for visualization using Sqoop.

oCreated custom User Defined Functions (UDFs) to extend Hive and Pig core functionality.

oEnabled ODBC/JDBC data connectivity to Hive tables and worked with tools like Tableau and Flink

Environment: AWS S3, Glue, AWS EMR, Glacier, Redshift, Snowflake, Spark SQL, Sqoop, Flink,

YARN, Kafka, MapReduce, Hadoop, HDFS, Hive, Tableau, Spotfire, HBase.

Education:

University of Texas, Arlington Dec 2020

Masters in Applied Computer Science

KLU University May 2015

Bachelor’s in Computer Science

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