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Data Engineer with 10+ years of experience in designing and delivering large-scale data applications leveraging Big Data technologies and Cloud based Data engineering platforms. Hands on experience on Unified Data Engineering with Azure Data Factory, AWS, GCP, Snowflake, Databricks, Designed and developed Databricks Notebooks leveraging Python, Apache Spark, and SQL to build scalable data pipelines. Designed and implemented end-to-end data processing pipelines using Azure Data Factory, Databricks, Azure Functions, Triggers and Azure Key Vault to address complex business use cases and enable real-time analytics and monitoring. Good understanding of Spark Architecture with Databricks, Structured Streaming. Setting Up Integration Azure Data Factory, AWS and GCP with Databricks Workspace for Business Analytics, Manage Clusters in Databricks and managing the Machine Learning Lifecycle. Implemented Data Encryption and Access Control Measures using Azure Key Vault, Azure AD, and Microsoft Defender for Cloud, securing sensitive data and credentials. Built a robust and scalable data pipeline using AWS services including S3, Glue, Redshift, Lambda, CloudWatch, Kinesis, Step Functions, and Secrets Manager to orchestrate ETL workflows, manage secure data access, and support business intelligence reporting. Designed and delivered fact and dimension tables to support BI reporting and executive-level visualization in Power BI and Tableau, enabling data-driven decision-making for key management. Skilled in query optimization, data workflows using Alteryx and data visualization presentations using Power BI, and Quick Sight. Built pipelines in ADF using Datasets/Linked Services/Pipeline to extract, load and transform data from various sources such as Azure SQL, Blob storage, Azure SQL Data warehouse, write-back tool, and backwards. Developed scalable ETL pipelines on GCP using Dataflow, Big Query, and Cloud Storage to ingest, process, and transform data from sources like Cloud SQL, on-premises databases, Pub/Sub, and SaaS platforms automated workflows with Cloud Functions and Cloud Composer. Built robust data pipelines in Snowflake using Streams, Tasks, and Snowpipe to extract, load, and transform data from diverse sources such as AWS S3, Azure Blob Storage, on-prem SQL systems, and third-party APIs; enabled near real-time ingestion and transformation for analytics and reporting. End-to-end data pipelines using AWS Glue, Lambda, and Step Functions to extract, transform, and load data from Amazon S3, RDS, Redshift, and external APIs, ensured data quality and orchestration for both batch and near real-time processing scenarios. Migrated on-premises data from SQL and Oracle to Azure Data Lake Storage (ADLS Gen2) using Azure Data Factory ensuring scalable and efficient cloud data integration. Good knowledge of batch and historical data processing using Hive, Pig, and Databricks, enabling retrospective trend analysis, advanced feature engineering, and generation of ML-ready datasets for predictive modeling. Proficient in implementing CI/CD frameworks for data pipelines using tools like Jenkins, ensuring efficient automation and deployment. Configured data quality checks using Great Expectations, providing real-time monitoring and automatic alerting when validation rules were violated. Proficient in cloud migration strategies with a focus on Azure, AWS, Snowflake and GCP, including Azure Migrate, Lift and Shift methodologies. Managed end-to-end deployment workflows for data processing jobs, ensuring smooth transitions from development to production environments using Bamboo. With experience in delivering business intelligence solutions, developing executive dashboards and self-service BI using Tableau, Power BI, Looker, and Looker Studio to visualize KPIs, operational metrics, and compliance outcomes. Proficient in sorting, analyzing, and integrating data using GCP (Big Query, Cloud Dataflow), AWS (Glue, Redshift), and Snowflake (SQL, Streams & Tasks, Snow pipe). Proficient in configuring Azure DevOps pipelines and GitHub for continuous integration, automated testing, and streamlined code delivery. Experienced in dimensional modeling, data migration, cleansing, and ETL processes for data warehousing. Skilled in statistical modeling, machine learning, and decision trees, with a strong foundation in ETL processes and data transformation in AWS, GCP, Snowflake and Azure. Experienced in developing, maintaining, and supporting data pipelines using Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Azure Synapse Analytics, IBM DataStage jobs, custom frameworks, and related technologies. Worked in the areas of analysis, design, development, production support and implementation phases of Datawarehouse and BI application. Extensively worked on Datawarehouse concepts like Data Modeling, ETL Jobs, Data Marts and ETL Framework. Have extensive experience with Power BI, encompassing data visualization, report creation, and dashboard development. Hands-on experience in designing and implementing ETL/ELT pipelines to ingest semi-structured and nested JSON data from MongoDB and MongoDB Atlas into cloud data warehouses like Snowflake. Proficient in utilizing Spark Core and Spark SQL scripts using Scala to accelerate data processing capabilities. Good Experience in SQL (SSIS, SSAS, SSRS), T-SQL, PLSQL, Unix, Microsoft Power BI, Office 365.


  Dynamic IT professional with over 20 years of experience, specializing in Data Warehousing and Business Intelligence applications. Proven expertise in business requirements analysis, application design, development, testing, and implementation of client/server Data Warehouse and Data Mart systems across Banking, Financial Services, Insurance, Pharmaceutical, Telecom, and Retail industries. Recognized for delivering robust solutions that enhance data-driven decision-making and operational efficiency. Career aspirations include leading innovative projects that leverage emerging technologies to further optimize business intelligence capabilities.
  Highly skilled Technical Lead Project Manager with background in overseeing complex technical projects and leading diverse teams. Strong understanding of technology, project management methodologies, and strategic planning to ensure successful project delivery. Known for excellent problem-solving skills and ability to deliver results under tight deadlines. Past work has demonstrated significant improvements in efficiency, productivity, and team collaboration.
  A strong background in agile methodologies and a proven track record of leveraging RESTful APIs to extract and ingest data into Cloud RDS, ensuring near real-time access. Core competencies include data management, cloud technology integration, and agile project execution. Committed to optimizing processes and enhancing system performance.
  15+ years of development and leadership experience in building successful ETL solutions for supporting data transformations and processing, using various ETL technologies such as Informatica PowerCenter, Azure Data Factory, and AWS Glue.
  Over six years of successful implementations of several projects in an onsite-offshore model.
  Results-driven software engineer with over 7 years of expertise in utilizing distributed version control systems, particularly GITHUB, to ensure a clean and centralized code base. Demonstrated proficiency in code management and collaboration across diverse teams, leading to enhanced project efficiency. Committed to leveraging advanced version control practices to optimize development workflows and drive innovation.
  6+ years of experience in migrating applications and data from on-prem to the cloud using cloud technologies.
  4+ years of experience working in Azure Cloud (ADF, SQL Server, ADO).
  4+ years of experience working with Snowflake Cloud Data Warehouse.
  Experienced data architect skilled in designing and implementing Dimensional Models, Star Schemas, and Snowflake Schemas. Proven ability to enhance data integrity and optimize database performance. Strong analytical skills complemented by a solid understanding of data warehousing principles. Aiming to leverage expertise to drive innovative solutions in data management.


Cloud Data Architect with 16 years of expertise in IT, healthcare, financial services, telecom, manufacturing, and pharmaceutical sectors. Skilled in gathering, storing, and evaluating semi-structured and structured data from cloud and on-premises sources. Experienced in authoring best practices standards and guidelines for data analytics design and development. Proficient in Azure platforms and a range of data tools and frameworks. Assisted multiple enterprises in their digital transformation journey. Strong leadership and cross-functional team management skills. Completed many data strategy implementations with high-performance throughput, data availability, time, cost, and scalability.

Around 18 years of experience in the areas of finance, royalty, credit cards, retail, and investment domains.
Expertise in data modeling, data analysis, data integration, star schema, snowflake schema, dimensions, and fact tables. Worked extensively with all Informatica components, including IDQ, Power Exchange, Power Center, IICS, and MDM implementations. Implemented data ingestion strategies in Snowflake using Python and DBT models and macros. Solid experience and understanding of implementing large-scale data warehousing programs and end-to-end data integration solutions on Snowflake Cloud, Azure Databricks, and Informatica PowerCenter integrated with multiple relational databases (MySQL, Postgres, Oracle, Sybase, SQL Server, DB2). Experience in data migration from DB2, Postgres DB, to Snowflake cloud data warehouse, and Azure SQL database. Experience in using Snowflake features: zero-copy cloning, data sharing, bulk loading, external tables, partitioning, and ETL workflows. Knowledge and experience in S3 AWS services, and managed policies for S3 buckets. Used S3 bucket and Glacier for storage and backup on AWS. Experience in granting permissions, managing resources, and providing permissions to users in AWS IAM. Experience in Python programming for data processing and handling data integration between on-prem and cloud databases or data warehouses. Designed Apache Kafka streaming to read data from various sources, and send it to data pipelines. Had knowledge of open-source Kafka by creating topics using consumers and producers to ingest data into applications. Experience in working with Unix Shell, Perl, and Python scripts. Proficient in using Python libraries, such as Pandas and NumPy, for data analysis. Experience in designing and building data architecture on Azure, and using its services like Azure Data Lake, Azure Databricks, and Azure SQL Data Warehouse. I used OpenAI to prepare business need statements based on keywords used in search optimization and ranking. Working on an AI model to create applications and APIs for vendors, reducing the workforce and time by more than 50%. Load tested the applications with virtual users ranging from 25,000 to almost 1 million. Designed the system architecture, implementation, and integration of microservices for real-time, customer-facing applications.

Arun Rajarajan

Summary

Overview

Work History

Onsite Architect | Mash

Onsite Architect | Accelerate

Onsite Architect | SAS to Informatica Conversion

Onsite Architect | Yellowbrick Migration

Onsite Lead

Offshore ETL Lead | Category Management Support

Education

Master of Computer Application -

BSc - Computer Science

Skills

Accomplishments

Timeline

Onsite Architect | Mash

Onsite Architect | Accelerate

Onsite Architect | SAS to Informatica Conversion

Onsite Architect | Yellowbrick Migration

Onsite Lead

Offshore ETL Lead | Category Management Support

Master of Computer Application -

BSc - Computer Science

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