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Click here or scroll down to respond to this candidate Niharsh ReddyDenver,CO | PHONE NUMBER AVAILABLE | EMAIL AVAILABLEPROFILE SUMMARYHighly skilled and results-oriented Data Engineer with experience in designing, developing, and maintaining robust data pipelines and architectures. Adept at transforming raw data into actionable insights through the application of advanced data processing techniques and tools. Skilled in statistical analysis, predictive modeling, and machine learning to drive business intelligence and decision-making. Proven ability to manage projects and collaborate with stakeholders, ensuring data quality and governance. Strong communication skills and a track record of delivering robust data solutions in agile environments. Proficient in a variety of programming languages, big data technologies, and cloud platforms, with a proven track record of optimizing data workflows and ensuring data integrity and security.CORE COMPETENCIES Skilled in developing and executing strategic data plans aligned with organizational goals. Lead and mentor a team of data engineers, providing guidance and fostering collaboration. Adept at data integration, modeling, and visualization using tools such as Tableau and Power BI. Well-versed in designing scalable data architectures to support complex business requirements. Able to analyze and address data engineering challenges to ensure data quality and integrity. Strong communication skills to interact effectively with cross-functional teams and stakeholders. Adept at crafting scalable, user-friendly solutions, incorporating user needs efficiently and securely.SKILLS HIGHLIGHTSData Pipeline Development Big Data Technologies ETL (Extract, Transform, Load) ProcessesData Warehousing Stakeholder Management Machine Learning/Business Intelligence
Data Modeling and Integration Distributed Computing Cloud Platforms (e.g., AWS, Azure, GCP)Adaptable and Flexible Agile Development Methodologies Database AdministrationBusiness Process Modeling Data Governance & Quality Assurance Real-Time Data ProcessingTECHNICAL SKILLS Programming Languages: Python, SQL, Java
Cloud Platforms: AWS (S3, Redshift, Glue, Athena, EMR, Lambda, RDS, EC2) Data Warehousing: Amazon Redshift, Snowflake, Google BigQuery ETL Tools: AWS Glue, Apache NiFi, Apache Airflow, Talend Big Data Technologies: Hadoop, Spark, Kafka Databases: MySQL, PostgreSQL, MongoDB, DynamoDB Data Visualization: Tableau, QuickSight, Power BI Version Control: Git, GitHub, Bitbucket CI/CD: Jenkins, Docker, Kubernetes Other: Terraform, CloudFormation, RESTful APIs Programming Languages: Python, SQL, Java
PROFESSIONAL WORK EXPERIENCEData Engineer Bank of America NOV 2022 TILL DATE Developed and maintained Python-based data pipelines to process large-scale datasets, ensuring data accuracy and availability for critical banking applications. Designed, built, and maintained efficient data pipelines to process and transform large data sets. Collaborated with data scientists to understand requirements and implemented data solutions that met business needs. Developed and managed data integration processes to ensure seamless data flow between systems. Leveraged AWS QuickSight for scalable, cloud-based data visualization, enabling dynamic reporting and analytics for banking operations. Developed a real-time data pipeline using Python, SQL, and AWS S3 to ingest, process, and store transaction data for a banking application. Optimized SQL queries and database schemas to enhance performance and reduce latency in data retrieval for real-time banking analytics. Ensured data quality and consistency across various data sources and storage solutions. Developed and orchestrated ETL workflows using AWS Glue, streamlining the extraction, transformation, and loading of data from diverse sources. Reduced storage costs by 20% through optimized data archiving and compression techniques. Implemented data security measures to protect sensitive information and ensured compliance with regulations. Optimized database performance by identifying and resolving bottlenecks in data processing workflows. Employed Git for version control, ensuring collaboration and code integrity across data engineering projects. Monitored data infrastructure and troubleshot issues to maintain system reliability and performance. Integrated Jenkins into the CI/CD pipeline, automating the deployment and testing of data engineering solutions. Utilized Docker and Kubernetes for containerization and orchestration of data engineering applications, ensuring scalability and efficient resource management. Improved data pipeline efficiency by 40%, reducing processing time from hours to minutes. Documented data engineering processes and created detailed technical specifications for future reference.Data Engineer Letsmobility Software Solutions JUN 2019 JUL 2021
Implemented data warehousing solutions using Amazon Redshift, enabling efficient querying and reporting of financial data. Automated data validation and monitoring processes using Python, improving data quality and reducing manual intervention. Assisted in developing and deploying Python and SQL-based data pipelines for various software solutions, including customer management and e-commerce platforms. Supported the migration of data workloads to AWS, collaborating with senior engineers to ensure smooth transitions. Contributed to the design and optimization of database schemas, improving query performance and reducing costs. Migrated on-premises data infrastructure to AWS, reducing operational costs by 30% and improving data accessibility. Collaborated with data scientists and business analysts to provide clean, reliable data for predictive modeling and regulatory reporting. Designed and implemented a data lake on AWS using S3, Glue, and Athena, enabling centralized storage and analysis of diverse data sources. Integrated the data lake with existing ETL workflows, facilitating seamless data ingestion and transformation. Created and maintained documentation for data engineering processes and infrastructure, ensuring knowledge transfer and consistency. Managed infrastructure as code using Terraform, automating the provisioning of AWS resources and improving deployment consistency. Implemented data warehousing projects on Snowflake, ensuring high availability and fast data retrieval for business intelligence and analytics teams. Implemented and managed data warehousing solutions using SQL-based platforms like Amazon Redshift and Google BigQuery, facilitating efficient data storage and retrieval.EDUCATION Master s in Business Analytics | 3.530 University of Colorado, Denver Bachelor s degree at MallaReddy College of Engineering and Technology, HyderabadLANGUAGESTelugu, Hindi, English (all advanced)CERTIFICATIONSAWS Certified Data Engineer Associate |
