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DEEPAKPHONE NUMBER AVAILABLE EMAIL AVAILABLEPROFILE SUMMARYData Engineer with 5 years of experience specializing in Python for data manipulation, SQL for database querying, and Scala/Java for scalable processing. Proficient in Apache Spark, Kafka, ETL tools, NoSQL databases, cloud platforms, and containerization for building efficient data pipelines and applications.Seeking a challenging position as a Data Engineer where I can leverage my expertise in Python, SQL, Scala/Java, and various data engineering tools to design and optimize data pipelines for insightful analytics and decision-making.Experienced Data Engineer with 5 years of hands-on experience in designing, developing, and managing robust data pipelines and architectures.Proficient in ETL Processes, leveraging tools such as Apache NiFi, Apache Airflow, and Talend to ensure seamless data extraction, transformation, and loading.Skilled in SQL and NoSQL Databases, including MySQL, PostgreSQL, MongoDB, and Cassandra, ensuring optimized data storage and retrieval.Expertise in Big Data Technologies, particularly Hadoop, Spark, and Kafka, for handling and processing large volumes of data efficiently.Proficient in Cloud Platforms, such as AWS, Google Cloud Platform, and Azure, utilizing services like S3, Redshift, BigQuery, and Data Factory for scalable data solutions.Strong Programming Skills in languages such as Python, Java, and Scala for data processing, automation, and analytics tasks.Experienced in Data Warehousing, with knowledge of Snowflake, Amazon Redshift, and Google BigQuery to build and maintain scalable data warehouses.Familiar with Data Modeling Techniques and tools such as ER/Studio, dbt, and Looker to design logical and physical data models.Proven Ability to Work in Agile Environments, collaborating with cross-functional teams to deliver high-quality data solutions in sprints.Strong Problem-Solving Skills, with a track record of identifying inefficiencies and implementing performance improvements in data processes.Excellent Communication Skills, enabling effective interaction with stakeholders to understand data requirements and deliver actionable insights..TECHNICAL SKILLS SETProgramming Language: Python, Scala, SQL,C,Java.Big Data Technologies: Hadoop, Spark, Hive, Pig, MapReduce, HBasePackages: ggplot2, Seaborn, NumPy, Pandas, MatplotlibCloud Platforms: AWS (EC2, Athena,S3, Redshift, SAILPOINT), Azure, GCP,Synapse,ADLA,ADLSDatabase: SQL Server, PostgreSQL, MySQL, SnowflakeData Visualization: Tableau, Excel, PowerBIETL Tools: SSIS, SSASData Pipelines: Apache Airflow, AWS Glue, ADFScripting: Shell Scripting, Batch ScriptingStreaming Technologies: Apache Kafka, Amazon KinesisContainerization and Orchestration: Docker, KubernetesVersion Control Systems : GitIssue Tracking and Project Management: JiraWORK EXPERIENCEData Engineer Capital One, USAJuly 2023 - PresentDesign, develop, and maintain scalable data pipelines to ingest, process, and store large volumes of data from various sources.Ensure data quality, integrity, and reliability through robust data validation and cleansing processes.Implemented and managed both SQL and NoSQL databases to store structured and unstructured data efficiently.Optimize database performance and query execution to support fast data retrieval and analytics.Develop and maintain ETL (Extract, Transform, Load) processes to integrate data from multiple sources into the data warehouse.Automate ETL workflows to ensure timely and accurate data availability for business intelligence and analytics.Design and implement data warehousing solutions to consolidate and organize data for reporting and analysis.Utilized Snowflake for building and optimizing data warehouse solutions, ensuring efficient data storage and retrieval for analytical purposes.Maintain and optimize the data warehouse architecture to support scalable and high-performance data operations.Implemented Kubernetes for container orchestration, managing microservices deployments, scaling, and ensure high availability of applications.Implement data security measures and ensure compliance with data privacy regulations and company policies.Monitor data access and usage to prevent unauthorized access and data breaches.Integrate data from various financial systems, third-party APIs, and data feeds into a centralized data platform.Experienced in leveraging AWS services for scalable data infrastructure, including S3, Redshift, EMR, RDS, Glue, with a focus on optimization, security, and automation.Ensure low-latency and high-throughput data processing on AWS to support real-time financial applications...Utilized Docker to containerize applications, streamlining development, testing, and deployment processes across multiple environments.killed in leveraging FastAPI to design and build robust, asynchronous APIs, utilizing modern Python features to achieve high throughput, low latency, and scalability for web applications and microservices.Data Engineer Verizon, India.Jan 2020- July 2022Developed robust data transformation processes utilizing AWS Glue to convert raw data into structured formats optimized for meaningful analytics and operational insights.Proficient in designing and optimizing data warehouses using Amazon Redshift, focusing on schema design, query optimization, and ETL processes for scalable analytics solutions.Experienced in utilizing Amazon S3 for scalable and secure data storage, implementing lifecycle policies, versioning, and access controls to support diverse data management needs effectively.Implemented automated data processing pipelines using AWS Lambda functions, optimizing scalability and reducing operational costs by automating resource provisioning and scaling based on real-time data demands.Established and enforced robust data governance policies and procedures on AWS, ensuring data accuracy, consistency, and reliability across all operations..Expertise in developing RESTful API integrations, with a strong preference for experience in SailPoint, ServiceNow, and AWS environments.Designed and implemented highly scalable and low-latency NoSQL database solutions using Amazon DynamoDB, optimizing performance and ensuring seamless scalability for mission-critical applications.Proficient in deploying and managing AWS EMR clusters for big data processing, utilizing Apache Spark and Hadoop to analyze large datasets efficiently.Developed and maintained scalable data pipelines on AWS using GLUE to process and analyze terabytes of customer data daily.Skilled in utilizing Informatica on AWS for data integration, ETL processes, and data quality management to support enterprise data solutions.Led and contributed to multiple AI/ML initiatives on AWS, applying algorithms and models to solve real-world problems.Demonstrated proficiency in designing, implementing, and optimizing real-time data streaming solutions using AWS Kinesis, ensuring scalability, reliability, and efficient data processing for high-throughput applications.Proficient in leveraging AWS Athena for ad-hoc querying and analysis of data stored in Amazon S3, optimizing query performance and reducing operational costs by eliminating the need for infrastructure management.Data Engineer Sarag Systems, India.Aug 2018  Dec 2019Design, implement, and maintain cloud-based data infrastructure using platforms like AzureDevelop scalable and efficient data pipelines to handle large volumes of data in a cloud environment.Lead data migration efforts from on-premises systems to cloud-based data warehouses and data lakes.Ensure data integrity and minimal downtime during migration processes.Develop and manage ETL processes to extract data from various sources, transform it according to business requirements, and load it into cloud-based storage solutions.Automate ETL workflows to improve efficiency and reduce manual intervention.Implement robust security measures to protect data in the cloud, including encryption, access controls, and monitoring.Ensure compliance with industry standards and regulations for data security and privacy.Utilized Databricks for data preprocessing, analysis, and visualization tasks, enabling streamlined insights extraction from large datasets.Work closely with data analysts, data scientists, and other stakeholders to understand data requirements and deliver solutions.Provide technical support and troubleshooting for cloud data infrastructure and pipelines.Proficient in Azure Data Lake Analytics (ADLA) and Azure Data Lake Storage (ADLS) for building scalable data processing pipelines, managing large datasets, and enabling efficient data analytics workflows.EDUCATIONMaster's in Information Systems and TechnologyUniversity of Missouri-St. Louis (UMSL), 2024Bachelor of Technology in Computer ScienceVellore Institute of Technology (VIT), Vellore, 2021