Summary
Overview
Work History
Education
Skills
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Rajesh Nallamothu

Summary

Over 5 years of progressive experience in IT, specializing in software development, data engineering, and business intelligence in hybrid (on-premises and cloud) environments. Proficient in designing and implementing advanced database solutions, ETL pipelines, and data models with Azure SQL Data Warehouse, Azure SQL, and Snowflake.

  • Demonstrated expertise in data governance, data quality, security, and integration, ensuring streamlined data processing and provisioning for enterprise-level projects.
  • Delivered high-impact data management solutions on Azure Cloud, translating complex analytical requirements into actionable designs, including data models, ETLs, and interactive dashboards.
  • Migrated and modernized on-premises databases to cloud-native architectures, improving scalability and accessibility.
  • Extensive experience in deploying self-service analytics dashboards across relational and non-relational databases, utilizing computing paradigms like In-Memory and Massively Parallel Processing.
  • Successfully executed and managed large-scale data initiatives, utilizing Agile methodologies across planning, design, and deployment phases.
  • Proficient in automation and CI/CD pipelines, leveraging Terraform, Azure DevOps, and CloudFormation for efficient development and deployment workflows.
  • Expertise in data visualization tools like Power BI and SSRS, integrating predictive analytics for actionable business insights.

Overview

6
6
years of professional experience

Work History

Data Engineering Consultant

Manulife
09.2022 - Current
  • Created reports using SSRS and Power BI
  • Developed ETL pipelines with Azure Data Factory ADF and SSIS
  • Wrote complex TSQL queries
  • Demonstrated strong consulting skills in data management, including data governance, data quality, security, data integration, processing, and provisioning
  • Led and delivered data management projects in Azure Cloud
  • Translated complex analytical requirements into technical designs, including data models, ETLs, and dashboards/reports
  • Deployed dashboards and selfservice analytics solutions on both relational and nonrelational databases
  • Designed and implemented end to end data pipelines using Azure Data Factory for orchestrating data movement and transformation tasks
  • Created data ingestion pipelines to load data from various sources, including Azure Blob Storage, Azure SQL Database, Azure Cosmos DB, and onpremises databases
  • Implemented data transformation activities using Azure Databricks notebooks or SQL transformations within ADF pipelines
  • Architected and implemented scalable data pipelines using Databricks and PySpark to process and analyze large datasets
  • Developed and optimized complex SQL queries to extract, transform, and load data into data warehouses
  • Collaborated with cross-functional teams to design and develop PowerBI dashboards, providing actionable insights to stakeholders
  • Integrated Azure Event Hub for real-time data ingestion and streaming analytics
  • Improved data quality and consistency by designing and implementing data validation and cleansing processes
  • Migrating on premises to Azure Synapse dedicated SQL pool and do lift and shift all existing on premises reports, ETL to the cloud
  • Experience in Migrating databases from On Premise SQL Server to ADLS using Self Hosted Integration Runtime
  • Extensive experience in Extraction, Transformation and Loading of data using SSIS from heterogeneous sources
  • Handled an ETL migration activity from ADF V1 to ADF V2
  • Experience working on CTEs and Stored Procedures, Query Tuning Skills
  • Thorough Knowledge on Data Warehouse concepts like Star Schema, Snow Flake, Dimension and Fact Tables
  • Led the development of an Automated Production Line Optimization System using Python, driving efficiency and productivity improvements in manufacturing operations
  • Engineered predictive maintenance solutions in Python, utilizing machine learning algorithms to develop optimization algorithms in Python to streamline production schedules and maximize throughput on the manufacturing line
  • Utilized Python for resource allocation optimization, ensuring efficient utilization of manpower and equipment resources
  • Designed energy-efficient algorithms in Python to optimize energy consumption within the manufacturing facility
  • Experience working on snowflake with external and internal stages
  • Experience in creating data pipelines through streams and tasks using snow pipe in Snowflake
  • Strong experience in migrating other databases to Snowflake
  • Work with domain experts, engineers, and other data scientists to develop, implement, and improve upon existing systems
  • Participate in design meetings for creation of the Data Model and provide guidance on best data architecture practices
  • Integrated C# modules for real-time data acquisition from sensors and PLCs to monitor machine health and production metrics
  • Designed customized visualizations using PowerBI's rich library of chart types and formatting options to tailor reports to specific stakeholder requirements
  • Configured PowerBI to automatically refresh data from source systems at regular intervals to ensure users have access to up-to-date information

Data Engineer / Senior Business Intelligence Engineer

Cyient
09.2020 - 06.2022
  • Developed data processing and analytics solutions using Apache Spark on Azure Databricks, leveraging its scalable and collaborative environment
  • Built and optimized Spark jobs for data preparation, cleansing, aggregation, and analysis
  • Integrated Azure Databricks with other Azure services like Azure Data Lake Storage, Azure SQL Database, and Azure Synapse Analytics for seamless data processing
  • Designed and implemented data warehousing solutions using Azure Synapse Analytics to support analytical workloads
  • Created and managed dedicated SQL pools and serverless SQL pools for data querying and analysis
  • Data engineering experience in Python, SQL and Relational database, Datawarehouse/Data-Lake
  • Designing relational schemas and Implementing data security
  • Used SQL server integration services (SSIS) for importing files and performing various Extract Transform and Load operations
  • Orchestration experience of data pipelines on-premise or on the cloud including automation Hands-on experience in ETL tools, frameworks, processes
  • Hands-on experience working on a data warehouse Hands-on experience working with multiple databases
  • Experience with Python, PySpark, Spark to write data pipelines and data processing layers
  • Proficient in creating Azure Data Factory pipelines for on-cloud ETL processing; copy activity, custom Azure development etc
  • Proficient in designing and implementing data entities in Azure Data Services like Azure SQL DWH, Azure SQL DB, Azure Data Lake store (ADLS), Cosmos DB
  • Strong knowledge in Azure Databricks, Azure Data Catalog, Event Grid, Service Bus, SQL and Synapse
  • Developed PowerBI dashboards to track individual and team sales performance metrics, including quotas, achievements, and commissions
  • Experience in data modelling and Proficient in SQL developer skills in writing stored procedures, functions, transformations etc
  • Demonstrate expertise in writing complex, highly-optimized SQL queries across large data sets
  • Experience with Data Governance (Data Quality, Metadata Management, Security, etc.)
  • Excellent understanding of relational and non-relational databases modelling
  • Proficiency in manipulating and combining large datasets from multiple sources
  • Implemented customer segmentation analysis in PowerBI to categorize customers based on purchasing behavior, demographics, and buying preferences
  • Built and managed data pipelines using Apache Spark and Hadoop for processing large datasets from multiple sources
  • Developed ETL processes to ingest, transform, and store data in Snowflake and Redshift data warehouses
  • Created and maintained data visualization solutions in PowerBI to provide business stakeholders with actionable insights
  • Consulting on Snowflake Data Platform Solution Architecture, Design, Development and deployment focused to bring the data driven culture across the enterprises
  • Develop stored procedures/views in Snowflake for loading Dimensions and Facts
  • Created geographical maps in PowerBI to visualize sales performance by region, enabling sales managers to identify high-performing areas and target marketing efforts effectively
  • Developed DAX queries in PowerBI to calculate key performance indicators (KPIs) such as sales growth rate, conversion rates, and customer lifetime value
  • Created pipeline analysis reports using DAX queries to track sales pipeline progress and identify areas for improvement
  • Implemented PolyBase to load data into Azure Synapse Analytics from external data sources like Azure Blob Storage and Azure SQL Database
  • Designed and implemented data integration solutions using Azure services such as Azure Data Factory, Azure Databricks, and Azure Synapse Analytics
  • Developed ETL and ELT processes to move and transform data between different data sources and destinations

Database Engineer

Citi
02.2019 - 09.2020
  • Assisted in the development of ETL pipelines using Talend and Apache Nifi
  • Supported the implementation of data integration solutions with Azure Event Hub for streaming data
  • Conducted data analysis and provided support in creating reports and dashboards in PowerBI
  • Participated in database design and maintenance, ensuring data quality and consistency
  • Collaborated with senior data engineers to troubleshoot and resolve data-related issues
  • Manage or create database procedures/functions, Jobs or any objects in database
  • Troubleshoot, fix and track automation/ETL issues
  • Write complex queries, views and transformations with T-SQL
  • Developing SSRS reports using Microsoft SQL
  • Experience with developing Business Intelligence dashboards using Power BI
  • Interacted with Business Analysts and stake holders to gather business requirements
  • Successfully delivered largescale data management initiatives covering the plan, design, build, and deploy phases, leveraging different delivery methodologies, including Agile
  • Expertise in data warehousing concepts, including star and snowflake schema
  • Defined parameters for parameterized reports and implemented cascading parameters
  • Created complex expressions, calculations, sorting, and filtering to enhance data presentation in reports
  • Created SSIS packages to extract data from Excel files, flat files, text files, and CSV files using various transformations
  • Worked on knowledge transfer and documentation of various jobs developed and deployed into production
  • Implemented data backup and recovery mechanisms in C# to ensure the integrity and availability of customer data in case of system failures or disasters
  • Developed features in C# for customers to contact customer support, raise queries, and receive assistance with banking-related issues directly through the online platform
  • Utilized C# to implement encryption and secure communication protocols to safeguard sensitive transaction data during online banking sessions
  • Implemented real-time transaction monitoring in Python to analyze customer transactions for signs of fraudulent activity
  • Leveraged Python to analyze behavioral biometrics data for user authentication and unauthorized access detection
  • Integrated an ATM locator feature using C# to help customers find nearby ATMs and branches for cash withdrawals and other banking services
  • Utilized Python libraries for geolocation tracking of transactions, flagging suspicious transactions occurring in unusual locations
  • Developed fraud risk scoring models in Python to prioritize investigation efforts based on the likelihood of fraud
  • Integrated data from diverse sources such as transactional databases, CRM systems, and external data feeds into the EDW using SQL's ETL (Extract, Transform, Load) capabilities
  • Designed and implemented normalized data models using SQL to ensure data consistency, integrity, and scalability within the EDW
  • Employed SQL queries and scripts to perform data cleansing, transformation, and enrichment processes to ensure data quality and consistency
  • Designed SQL-based solutions for incremental data loading to efficiently handle large volumes of data updates while minimizing downtime and resource consumption
  • Integrated SQL-based reporting tools and BI platforms to create interactive dashboards and reports for visualizing insights and trends derived from EDW data
  • Provided SQL-based ad hoc querying and analysis capabilities to business users and data analysts, empowering them to explore and analyze data independently
  • Implemented account statement generation features in C# to enable customers to download and view detailed account statements for auditing and reconciliation purposes
  • Integrated compliance monitoring features using Python to ensure adherence to regulatory requirements in fraud detection and prevention
  • Implemented transaction categorization features in C# to automatically categorize transactions into predefined categories for expense tracking and analysis
  • Designed an intuitive user interface using Python frameworks like Flask or Django for bank personnel to interact with the fraud detection system
  • Use customer requirements to improve functionality (speed, performance / usability)
  • Created, tested and implemented SQL backup strategy based on the business needs, utilize the combination of full, differential and transactional log backup to ensure all necessary business data is properly backed up
  • Provided back-end support for functional testing and performance testing
  • Developed scripts to migrate data from multiple sources to desired destination using ETL tools
  • Created detailed design and requirements documents with logic to help team members understand the requirements and design
  • Used SSRS to create, execute, and deliver tabular, matrix, and charts reports
  • Involved in usage of various SSIS components like Slowly Changing Dimension, Conditional Split, Merge, Merge Join, Multicast, Union All, Sort, Derived column, SQL execution task, Variables, and Error Handling before loading data into the Data warehouse
  • Designed custom Dimensions and Facts Tables to extend data warehouse
  • Worked on the project that involved development and implementation of a data warehouse
  • Conducted system tests, troubleshoot customer issues and correct database defects
  • Transferred data from various data sources/business systems including DB2, MS Excel, MS Access, Flat Files etc
  • To SQL Server using SSIS Packages and using various features like Excel source, Flat file source, transformation etc
  • Created derived columns from the present columns for the given requirements
  • Established SQL-based data lineage and traceability mechanisms to track the origin, transformation, and usage of data within the EDW environment
  • Used SQL Server to load tables in support of de-coupled, pluggable architecture to manage data flows between service providers and LIPA

Education

Bachelor of Science - Information Technology

R.V.R. & J.C. COLLEGE OF ENGINEERING
GUNTUR, AP

Skills

    Data Integration & ETL: SSIS package version control, Azure Data Factory features, Talend, Informatica, Azure Data Lake integration with Azure DevOps, Azure Data Bricks integration, Delta lake, Azure Kubernetes Service (AKS), Apache Airflow

    Big Data & Data Engineering: PySpark, Databricks, Azure Synapse, Azure Functions, Development and optimization of data pipelines, Data Lake, Amazon EMR, Azure HDInsight, AWS Glue, Apache Oozie

    Business Intelligence: Power BI real-time streaming, Amazon QuickSight, AWS CloudFormation, Power BI custom reports, BI data exploration tools, Power BI data sets with row-level security

    Database Management: Database connection pooling, Snowflake Infrastructure, Azure Key Vault event grid, Blob Storage versioning, Data compression, Azure Cosmos DB, Encryption in Azure Data Factory, Amazon S3, Amazon Redshift

    Reporting: SSRS report deployment, SSRS report navigation, Report snapshots, Tableau, Power BI performance monitoring, Excel, PowerPoint

    Cloud Technologies: Azure Data Factory, Databricks, Azure Data Lake Storage, SQL Database, Azure Analysis Services, Azure Storage Account, Blob Storage, Amazon Athena, AWS, GCP

    Reporting Tools: Power BI, SSRS

    Tools and Packages: SQL Server Management Studio, DBT, Visual Studio, Enterprise Manager, SQL Profiler, SQL Server Data Tools, DTS, Report Builder

    Database Technologies: SQL Server, MySQL, MS Access, MongoDB, NoSQL, Oracle, PostgreSQL, RDBMS, AWS DynamoDB

    Scripting: SQL, Python, PowerShell, Linux bash scripting, TSQL, Scala

    Change Management Tools: Team Foundation Server (TFS), GitHub, Jira, Docker, Jenkins, Kanban

    Operating Systems: Windows Server 2012, MS DOS, UNIX, Linux

    Languages: R, Python, Java, JSON, HTML

Timeline

Data Engineering Consultant

Manulife
09.2022 - Current

Data Engineer / Senior Business Intelligence Engineer

Cyient
09.2020 - 06.2022

Database Engineer

Citi
02.2019 - 09.2020

Bachelor of Science - Information Technology

R.V.R. & J.C. COLLEGE OF ENGINEERING

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Rajesh Nallamothu