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With Bachelor's degree in Computer Science & Engineering along with 3+ years of experience as a data engineer, have received SPOT award from LTIMindtree for completing all the ETL tasks with atmost accuracy and speed. Proficient at detail-oriented designing & developing jobs which align with business requirements. Accustomed to working closely with business analysts, data analysts and data modelers to understand industry requirements in order to develop robust ETL jobs.

Delivered scalable, high-performance data engineering solutions with over 11 years of IT expertise in Data Engineering, Data Warehousing, and Big Data. Leveraging 5+ years of experience in data engineering and 4+ years in data warehousing across healthcare, finance, retail, and manufacturing domains. Designed, built, and optimized large-scale ETL/ELT pipelines using Azure Data Factory, Azure Databricks, AWS Glue, Snowflake, and Apache Spark. Implemented real-time data ingestion and analytics pipelines leveraging Kafka, Spark Streaming, Azure Event Hubs, and AWS Kinesis. Developed reusable, parameterized pipelines to reduce development time and improve maintainability. Created optimized data models and schemas using dimensional modeling techniques (star schema, snowflake schema). Applied advanced performance tuning techniques such as partitioning, bucketing, indexing, caching, and workload management. Integrated structured, semi-structured, and unstructured data from diverse sources including RDBMS, APIs, and cloud storage. Automated ETL workflows using Apache Airflow, Oozie, Control-M, IBM Tivoli, Jenkins, and Azure DevOps pipelines. Utilized advanced Snowflake features including SnowSQL scripting, time travel, zero-copy cloning, and complex SQL functions. Built CI/CD frameworks for automated deployment, testing, and version control of data pipelines using Git, Jenkins, and Azure DevOps. Developed robust data quality and validation frameworks to ensure dataset integrity and reliability. Managed large, distributed clusters and fine-tuned Spark jobs for optimal performance and scalability. Designed real-time analytics dashboards with Power BI and Tableau for actionable business insights. Wrote complex SQL queries, stored procedures, triggers, and functions for data transformation and reporting. Processed geospatial and time-series datasets using specialized algorithms and frameworks. Created monitoring frameworks using AWS CloudWatch, Azure Monitor, and custom logging systems. Implemented data security and governance measures including RBAC, encryption, GDPR, and HIPAA compliance. Integrated hybrid data sources between on-premises and cloud environments. Mentored and guided junior data engineers, fostering collaborative learning. Collaborated with stakeholders to translate business requirements into scalable technical solutions. Operated effectively within Agile and Scrum frameworks (sprint planning, daily stand-ups, retrospectives). Delivered high-quality solutions on time while balancing technical and business priorities. Researched and adopted emerging data engineering tools and technologies. Transformed raw data into meaningful insights that drive business decisions. Change my professional summary for a business analyst position Senior engineering professional with deep expertise in data architecture, pipeline development, and big data technologies. Proven track record in optimizing data workflows, enhancing system efficiency, and driving business intelligence initiatives. Strong collaborator, adaptable to evolving project demands, with focus on delivering impactful results through teamwork and innovation. Skilled in SQL, Python, Spark, and cloud platforms, with strategic approach to data management and problem-solving.

Experienced data analytics and engineering professional with 5+ years of expertise in leveraging data insights to drive strategic decision-making across multiple business functions. Proficient in Python and SQL for data analysis, as well as Power BI and Tableau for creating interactive dashboards and reports. Skilled in utilizing machine learning techniques for predictive analytics. Recognized for automating reporting processes and improving system performance through innovative solutions.

Experienced AWS Data Engineer with over 14 years of dedicated expertise in designing, implementing, and optimizing data solutions on the Amazon Web Services (AWS) platform. Proficient in leveraging a diverse skill set encompassing data architecture, ETL processes, data warehousing, and analytics to drive actionable insights and enhance business intelligence capabilities. Demonstrated track record of delivering high-quality, scalable data pipelines and solutions that meet the evolving needs of diverse industries. Adept at collaborating with cross-functional teams to translate business requirements into technical solutions, ensuring alignment with strategic objectives and delivering measurable value. Proven ability to stay abreast of emerging technologies and best practices in the rapidly evolving field of cloud-based data engineering, while maintaining a focus on innovation and continuous improvement. Dedicated to driving organizational success through the effective utilization of data as a strategic asset.

Senior engineering professional with deep expertise in data architecture, pipeline development, and big data technologies. Proven track record in optimizing data workflows, enhancing system efficiency, and driving business intelligence initiatives. Strong collaborator, adaptable to evolving project demands, with focus on delivering impactful results through teamwork and innovation. Skilled in SQL, Python, Spark, and cloud platforms, with strategic approach to data management and problem-solving.

Nicholas Fazio

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Senior Data Engineer

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Senior Data Engineer

Bachelor of Science - Computer Science

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