Azure Data Power Bi

Name: GURU RELANGI

Email: *******.*************@*****.***

Phone: 984-***-****

Professional Summary

Around 10 years of extensive experience in database design and development using MS SQL Server, Tableau, Power BI.

Experience in Data Visualization including producing tables, graphs, listings using various procedures and tools such as Tableau.

Experience in Text Analytics, developing Data Mining solutions to various business problems and generating Data Visualizations using R and Python.

Experience in creating visualizations, interactive dashboards, reports and data stories using Tableau, Power BI and MicroStrategy.

Experience with statistical programming languages such as R, Gplot and Python.

Experience in OLTP and OLAP design, development, testing, implementation and support of enterprise data warehouse.

Extract The data from Source Systems to Azure Data Storage services using a combination of Azure Data Factory, T-SQL, Spark SQL, and U-SQL Azure Data Lake Analytics.

Architect & implement medium to large scale BI solutions on Azure using Azure Data platorm services (Azure Data Lake, Data Factory, Data Lake Analytics, Stream Analytics, Azure SQL DW, Databricks).

Configure pipelines for automated data validation, ETL jobs, and reporting tools using tools like Jenkins, Azure DevOps, GitLab CI, or AWS CodePipeline.

Ensured cost-effective analytics by monitoring Athena query costs and implementing efficient data modeling and access patterns.

Designed and developed scalable ELT pipelines in Matillion ETL for Snowflake, processing large volumes of customer and network data.

Experience in developing and scheduling the Spark applications in data bricks using PySpark and Scala for data extraction, transformation, and aggregation.

Work with Docker and Kubernetes to deploy analytics tools or models as microservices or scheduled jobs.

Experience and high proficiency in writing complex SQL queries like stored procedures, triggers, joins and subqueries along with that used MongoDB for extraction data.

Experience in NoSQL databases like MongoDB (RoboMongo) and exposure in Cassandra.

Experienced in python data manipulation for loading and extraction as well as with python libraries such as NumPy, SciPy and Pandas and Spark.

Experience in Amazon Web Services (AWS) Cloud services like EC2, S3, IAM and Cloud Watch.

Experience with data visualization using tools like Gplot, Matplotlib, Seaborn, Tableau, R and using Tableau software to publish and presenting dashboards, storyline on web and desktop platforms.

Expertise in Excel, Pivot Tables, VLOOKUP and other advanced functions.

Integrated Lambda with S3, Kinesis, and DynamoDB to automate data ingestion workflows, reducing manual overhead and latency.

Integrated Athena with QuickSight to create interactive dashboards without moving data to traditional warehouses.

Designed and maintained scalable Redshift clusters to support complex analytical queries on terabytes of mobile customer and network data.

Built Redshift ETL pipelines using AWS Glue and Lambda for batch loading of transformed data from S3 and RDS sources.

Experience and Technical proficiency in Designing, Data Modeling Online Applications, Solution Lead for Architecting Data Warehouse/Business Intelligence Applications.

Experience in Designing and Building the Dimensions and cubes with star schema using SQL Server Analysis Services (SSAS).

Designed and deployed serverless ETL pipelines using AWS Lambda to process and transform streaming data from mobile network logs in real time.

Experience with databases like Snowflake, MySQL, Oracle, etc.

Experience in using SSIS to create ETL packages to validate, extract, transform and load data to data warehouse databases, and process SSAS cubes to store data to OLAP databases.

Experience in using various stages like Join, Merge, Lookup, Remove Duplicates, Sort, Filter, Dataset, Modify and Aggregator.

Experience in Data Warehousing applications, responsible for the Extraction, Transformation and Loading (ETL) of data from multiple sources into Data Warehouse.

Experience in Reporting, Data visualization skills using Tableau and advanced MS-Excel, Google Sheets and strong experience in databases such as Teradata, Oracle, MYSQL and MS SQL server.

Experience with big data tools like Hadoop, Spark, Hive, Pig, PySpark, Spark SQL, PySpark.

Experience in using GIT Version Control System. Implemented Kafka for building data pipeline and analytic modules.

TECHNICAL SKILLS:

Data Modelling Tools

Erwin, ER/Studio, Power Designern Dimensional Data Modeling using Erwin, Data Warehousing

Project Management

MS Project

Methodologies

SDLC, Agile, Waterfall, RUP.

Hadoop Distribution

Cloudera, HortonWorks

Cloud

AWS, Azure, Snowflake.

Databases

Oracle, MS Access, MySQL, SQL Server, Teradata, DB2,Snwoflake

ETL Tools

Informatica PowerCenter, Cognos

Languages

PL/SQL, T-SQL, MS SQL

OS

Windows, UNIX, Linux

Others

MS Project, MS Visio, MS Office, TOAD

OLAP Tools

Business Objects, Microsoft Analysis Services,etc

Education:

Master of Technology Management (JAN 2022- AUG 2023)

Lindsey Wilson University, Kentucky

Bachelors of Technology (JUL 2012- MAY 2016)

JNTU University, Hyderabad, India

PROFESSIONAL EXPERIENCE:

Client Name: T Mobile, Parsippany, NJ (MAY 2024 – TILL DATE)

Role: Sr Data Engineer

Responsibilities:

Extract transform and load data from Source Systems to Azure Data Storage services using a combination of Azure Data Factory, T-SQL, Spark SQL and U-SQL Azure Data Lake Analytics.

Used Agile methodology to build the different phases of software development life cycle.

Data Imgestion to one or more Azure Services-(Azure Data Lake, Azure Storage, Azure SQL, Azure DW) and processing the data in Azure Databricks.

Developed modular, reusable Lambda functions in Python to support scalable microservices architecture for data engineering workloads.

Development of ETL pipelines for transferring data from diverse sources to many layers in S3 using AWS Glue and Databricks

Created an aggregated report daily for the client to make investment decisions and help analyze market trends.

Integrate BI tools (Power BI/Tableau) with CI/CD pipelines for report updates and dashboard deployments.

Integrated Matillion with AWS S3, Redshift, Snowflake, and API-based data sources used within T-Mobile's data architecture.

Integrated Redshift with BI tools like QuickSight for end-to-end data visibility and near-real-time analytics delivery.

Created orchestration jobs to schedule and monitor end-to-end data workflows using Matillion Scheduler and external tools like Airflow.

Used tools like Apache Atlas, DataHub, or Azure Purview for data governance and lineage integration in DevOps pipelines.

Enabled row-level security (RLS) in QuickSight to control data visibility for different user groups while maintaining performance

Handled job dependency management and alerting using Matillion’s built-in features.

Implemented automated error handling and retry mechanisms in Lambda to ensure fault tolerance and reduce data loss across data pipelines.

Modified existing dashboards as per new requirements in Power BI .

Clean data and processed third party spending data into maneuverable deliverables within specific format with Excel macros and python libraries such as NumPy, SQL Alchemy and matplotlib.

Develop and maintain data models that accurately represent the structure, relationships, and attributes.

Developed Data visualizations (Bar charts, scatter plots, Pie charts, stacked bar charts etc.,) using SQL, Python and Jupyter.

Implemented CloudWatch dashboards and alarms to monitor end-to-end performance of real-time ETL pipelines processing telecom usage and billing data.

Used CloudWatch Logs and Insights to diagnose issues in Lambda, Glue, and Redshift jobs, enabling faster root cause analysis and reducing downtime.

Implemented Extract, Transform, Load (ETL) processes to efficiently move and transform data between Redshift and Snowflake.

Data Quality Assurance Collaborate with cross-functional teams to understand their data needs and translate business requirements into data models.

Created interactive Dashboards on desktop platform to visualize the data by using Tableau desktop.

Used Spark and Spark SQL for data integrations, manipulations. Worked on a POC for creating a docker image to run the model.

Extracted and loaded CSV files, json files data from AWS S3 to Snowflake Cloud Data Warehouse

Worked closely with Business Users in identifying the gaps between existing code and the business requirements in the ETL projects.

Documented all programs and procedures to ensure an accurate historical record of work completed on assigned project as well as to improve quality and efficiency.

Scheduled CloudWatch Events to automate data refresh tasks and pipeline orchestration, ensuring reliable data availability for T-Mobile reporting systems.

Assist with any problems that may emerge in the new Snowflake environment after the migration.

Implemented automated IAM role provisioning using Infrastructure as Code (IaC) tools to streamline onboarding and reduce human error.

Create and maintain comprehensive documentation for data models, including data dictionaries, metadata, and data lineage.

Implemented various KPIs and prepared Invoice dashboards with MicroStrategy.

Created SSIS Packages by using transformations like Derived Column, Sort, Lookup, Conditional Split, Merge Join, Union and Execute SQL Task to load into database.

Worked on development of data warehouse, Data Lake and ETL systems using relational and non relational tools like SQL, NoSQL.

Designed My SQL database schema, Mongo Documents to store the required data.

Worked in all phases of research like Data Cleaning, Data Mining, Feature Engineering, Developing tools, Validation, Visualizations and performance monitoring.

Automate different workflows, which are initiated manually with Python scripts and Unix shell scripting.

Leveraged Amazon Athena to run serverless SQL queries on large volumes of S3-stored mobile usage and billing data, significantly reducing data retrieval times.

Environment: Hadoop,MS Visio, MS Excel, Teradata, ER/Studio, Tableau, Power BI,Erwin,Snwoflake,MS Access, Oracle, Toad, UNIX, Windows, SQL, PL/SQL, Power Designer, Informatica, Unix, Agile.

Client Name: UPS, NJ (APRIL 2023 – MAY 2024)

Role: Sr. Data Engineer

Responsibilities:

Build various life cycles of project using Agile Methodology.

Performed Data Cleaning, Feature Scaling, and Feature engineering using Python packages such as Pandas, NumPy, Matplotlib, SQL Alchemy, Sci-kit Learn.

Monitor products' metrics by extracting large scale key data sets using SQL/R/Python/Hive/Spark, ensure data quality with the understanding of business ecosystems,

Developed detailed ER/Studio diagram and data flow diagram using modeling tools following the SDLC structure.

Integrated data from diverse sources including Oracle, SAP, AWS S3, REST APIs, and flat files using Matillion components.

Designed and developed scalable ETL/ELT workflows in Matillion ETL for Snowflake to process large volumes of logistics and shipping data for UPS.

Configure and maintain CI/CD pipelines for ETL (Extract, Transform, Load) workflows using tools like Jenkins, GitLab CI, Azure DevOps, or AWS CodePipeline.

Designed and enforced fine-grained IAM roles and policies to control access to sensitive delivery, shipment, and customer datasets across AWS services.

Audited and optimized IAM permissions across data engineering accounts to align with UPS’s internal security and compliance standards.

Configured CloudWatch metrics, dashboards, and alarms to monitor data pipelines and detect anomalies in real-time across UPS logistics workflows.

Developed custom CloudWatch log filters and insights to trace issues in Lambda, Glue, and Redshift jobs, reducing incident resolution time by 40%

Document data workflows, schema changes, and CI/CD pipeline configurations.

Tuned Lambda function performance with appropriate memory and timeout settings, improving processing speed by 30% for real-time analytics use cases

Develop and maintain data models that accurately represent the structure, relationships, and attributes.

Built reusable Matillion Orchestration Jobs for job scheduling, error handling, logging, and notifications via Slack and email.

Automated IAM role provisioning for new services and team members using Terraform and CloudFormation to support DevSecOps workflows.

Conducted periodic reviews of IAM roles and integrated logging with CloudTrail to monitor access patterns and flag potential security risks.

Used Matillion Project Exports in conjunction with Git for version control and CI/CD deployment pipelines.

Integrate automated testing frameworks into the CI/CD pipeline to validate data accuracy and pipeline integrity.

Developed and maintained reusable Athena views and SQL scripts for business stakeholders to track shipping KPIs and route efficiency.

Enabled cross-team reporting by integrating Athena with AWS Glue Data Catalog for centralized schema management.

Work with DevOps engineers to containerize data analysis scripts and ML models using Docker and orchestrate them via Kubernetes.

Ensured secure handling of sensitive UPS data using encryption, role-based access control, and Snowflake masking policies through Matillion.

Implemented scheduled CloudWatch Events to trigger automated pipeline steps, improving the efficiency of time-based data processing tasks.

Optimize data models for performance by designing efficient data storage structures, indexing strategies, and query optimization techniques.

Data Manipulation and Aggregation from different source using Nexus, Toad, BusinessObjects, PowerBI and SmartView.

Involved in gathering requirements while uncovering and defining multiple dimensions. Extracted data from Oracle database using SQL and performed data analysis.

Debugged many PL/SQL packages procedures, function, cursors and types for application.

Handling data and performing creating, reading, updating and deleting (CRUD) operations on MongoDB.

Used Anaconda Navigator an open-source tool for running Python in Jupyter notebook and Spyder.

Extensively used MS Access to pull the data from various data bases and integrate the data.

Environment: Tableau, Power BI, Databricks,Microsoft Excel, MS SQL, Power Designer, SAS, Teradata, ETL, SSIS, SQL, Erwin, ER/Studio, Oracle, MS Visio.

Company: INFOSYS, INDIA (MAY 2019 – OCT 2021)

Client Name: EBSCO

Role: Data Modeler/Data Analyst

Responsibilities:

Worked in Agile environment, with an ability to accommodate and test the newly proposed changes at any point of time during the release.

Performed exploratory data analysis like statistical calculation, data cleaning and data visualizations using NumPy, Pandas, SQL Alchemy, Scikit Learn and Matplotlib.

Improved the current forecast accuracy in R.

Read the Parquet and csbv files from S3 after applying the business logic and upload the output back to S3 using Pandas.

Design, configure, and maintain CI/CD pipelines for data analytics workflows using tools like Jenkins, GitLab CI, Azure DevOps, or AWS CodePipeline.

Automate deployment of data models, ETL/ELT scripts, and reporting dashboards.

Integrate testing and validation steps (unit, integration, regression) for data pipelines into the CI/CD workflows.

Track CI/CD metrics (e.g., build success rate, deployment frequency) and optimize performance.

Utilized Athena to query semi-structured delivery, route, and customer data stored in S3, enabling quick ad hoc analysis without provisioning infrastructure.

Implemented number of Natural Language process mechanism for Chart Bots.

Developed Tableau visualizations and dashboards using Tableau Desktop.

Explore data in a variety of ways and across multiple visualisations using Power BI.

Extensively used Erwin to model and transform date requirements in to data models and maintaining the database schema.

Monitor data pipeline performance and automate alerting and logging within the CI/CD pipeline.

Worked with project team representatives to ensure that logical and physical ER/Studio data models were developed in line with corporate standards and guidelines.

Written MapReduce code to process and parsing the data from various sources and storing parsed data into HBase and Hive using HBase - Hive Integration.

Migrated three critical reporting systems to Business Objects and Web Intelligence on a Teradata platform.

Optimize data models for performance by designing efficient data storage structures, indexing strategies, and query optimization techniques.

Develop business plan recommendations based on potential risks and returns.

Generated PL/SQL scripts for data manipulation, validation and materialized views for remote instances.

Provide support for analytics platforms (e.g., Tableau, Power BI, Looker) deployment via CI/CD.

Document CI/CD processes and ensure team onboarding to DevOps best practices.

Worked with NoSQL databases like HBase and MongoDB. Time Series Analysis -ARIMA, Neural Networks, Sentiment Analysis, Forecasting and Text Mining.

Used Python to save and retrieve data files from Amazon S3 buckets.

Conducted Exploratory Data Analysis using Python Matplotlib and Seaborn to identify underlying patterns and correlation between features.

Worked on improving performance of existing Pig and Hive Queries.

Create and maintain comprehensive documentation for data models, including data dictionaries, metadata, and data lineage

Used Python Matplotlib packages to visualize and graphically analyses the data.

Used MS Excel, MS Access and SQL to write and run various queries.

Environment: Oracle, SQL, Microsoft Visio, MS Office, Teradata, MS Project, Erwin, ER/Studio

COMPANY: ACCENTURE, INDIA (JULY2017- MAY 2019)

Client Name: JOHNSON & JOHNSON

Role: Data Modeler/Data Analyst

Responsibilities:

Implemented Agile Methodology for building an internal application.

Worked on requirements gathering, analysis, design, change management and deployment.

Designed, Implemented and automated modelling and analysis procedures on existing and experimentally created data using Python packages like Pandas, NumPy, Matplotlib, Scikit Learn.

Developed Tableau and Microsoft Power BI Dashboards to showcase the result of data analysis from the database.

Optimized existing process in MS Excel using Python and Tableau to deliver end- to- end business intelligence solutions.

Collaborate with data modelers, ETL developers in the creating the Data Functional Design documents.

Repair damaged or malfunctioning equipment and perform routine maintenance.

Work with process owners to identify and assess appropriate automation use cases.

Worked with data analysis using Matplotlib and seaborne libraries to do data visualizations for better understanding.

Created a framework using Matplotlib, dash and flask for visualizing the trends and understanding patterns for each market using the history data.

Integrate Data stage Metadata to Informatica Metadata and created ETL mappings and workflows.

Used python APIs for extracting daily data from multiple vendors.

Prepared Scripts in Python and Shell for Automation of administration tasks.

Developed complex database objects like Stored Procedures, Functions, Packages and Triggers using Oracle Database, SQL and PL/SQL.

Worked in importing and cleansing of data from various sources like Teradata, Oracle, flat files, SQL Server with high volume data.

Environment: Teradata, Hadoop, Informatica, Business Objects, Oracle, SQL, MS Visio, Tableau, UNIX Shell Scripting.

COMPANY: ACCENTURE, INDIA (JUN 2015 – JULY 2017)

Client Name: LAFARGE

Role: Data Analyst

Responsibilities:

Used Agile methodology and SCRUM process for project developing.

Worked with Data Warehouse team in developing Dimensional Model and analyzing the ER-Diagrams.

Responsible for building data analysis infrastructure to collect, analyze, and visualize data.

Generating various reports (graphical) using Python packages like NumPy, matplotlib.

Implemented Data Exploration to analyze patterns and to select features using Python SciPy.

Perform data quality control and assurance and handle quality issues.

Used the SQL Server profiler to capture and store the execution plan. Created necessary indexes.

Designed and developed ETL packages using SSIS to create Data Warehouses from different tables and file sources like Flat and Excel files, with different methods in SSIS such as derived columns, aggregations, Merge joins, count, conditional split and more to transform the data.

Used Informatica- Power center for extracting, transforming and loading

Interacted with Business analysts to understand data requirements to ensure high quality Data is provided to the customers.

Designed and developed an end-to-end agent exception reporting, analysis and testing.

Environment: Erwin, Informatica, ETL, Oracle, SQL, MS Visio, MS Office.

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