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9 years of IT Experience in Diverse Domains: Extensive background in end-to-end data analytics solutions encompassing Big Data, Hadoop, Informatica, Data Modeling, and System Analysis across Banking, Finance, Insurance, and Telecom sectors.

18 years of experience primarily in Banking and Financial Services, with strong expertise in FR 2052a FED Regulatory Reporting (5G & 6G), Analytics, and Data Governance. Proven track record in the design, development, and implementation of Cloud Data Lake, Data Mesh, Data Warehouse, and Business Intelligence solutions. Possesses strong technical, analytical, and functional skills, with end-to-end ownership across SDLC and Agile methodologies, including requirements analysis, documentation, architecture design, development, testing, implementation, production support, incident management, root cause analysis, and real-time debugging. Designed and delivered cloud-native solutions with a strong focus on engineering excellence, automation, innovation, and cross-team collaboration. Continuously evaluated and adopted new technologies, tools, and working practices, demonstrating agility and a strong learning mindset. Brought a curious, questioning approach to solution design, contributing innovative ideas and improving architectural and operational outcomes. Triaged complex production issues, performed root cause analysis (RCA), and made decisive, data-driven decisions under high-pressure scenarios. Acted confidently in break-glass production incidents, restoring services and minimizing customer impact during critical outages. Designed and implemented scalable solutions using AWS services, including compute, storage, networking, containers, and serverless frameworks. Built and deployed applications using Infrastructure as Code (IaC) tools such as Cloud Formation, Terraform, Ansible, and ARM, ensuring repeatability and compliance. Applied object-oriented principles and design patterns to develop maintainable, extensible, and high-performing applications. Developed and deployed containerized applications, leveraging Docker and Kubernetes, with strong experience deploying workloads on Amazon EKS. Implemented CI/CD pipelines using Jenkins and Git-based workflows, enabling automated build, test, and deployment processes. Collaborated effectively with distributed teams and stakeholders, both in-person and virtually, building trusted and productive working relationships. Worked with enterprise database technologies including Oracle, PostgreSQL, and SQL Server to support transactional and analytical workloads. Defined and implemented cloud reliability, resiliency, and observability strategies, ensuring high availability and performance of Tier-3 critical systems. Established and enforced engineering standards and best practices, contributing to increased engineering maturity and operational stability. Deployed and managed LLM-based solutions, including Retrieval Augmented Generation (RAG) architectures in cloud environments. Built full-stack AI-powered applications, integrating LLMs with backend services and cloud infrastructure. Applied best practices in prompt engineering, data privacy, hallucination mitigation, bias awareness, token usage, and cost optimization. Demonstrated understanding of GenAI modalities, determinism vs. randomness, and agentic behavior in production systems. Developed AI workflows and services using object-oriented Python, ensuring scalability, reliability, and maintainability. Data engineering professional poised to add significant value through comprehensive experience in developing scalable data solutions. Noted for strong team collaboration and adaptability in fast-paced environments. Reliable in driving results with key skills in data modeling, ETL processes, and cloud-based data platforms. Experienced with building and maintaining data pipelines to ensure seamless data flow. Utilizes advanced knowledge of big data technologies to drive data-driven decision-making. Track record of enhancing data architecture for improved performance and reliability. 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. Diligent [Desired Position] with robust background in data engineering and proven ability to design and implement complex data pipelines. Successfully contributed to optimizing data architecture and enhancing data processing efficiencies. Demonstrated expertise in big data technologies and proficiency in Python and SQL. Responsive expert experienced in monitoring database performance, troubleshooting issues and optimizing database environment. Possesses strong analytical skills, excellent problem-solving abilities, and deep understanding of database technologies and systems. Equally confident working independently and collaboratively as needed and utilizing excellent communication skills. Detail-oriented [Job Title] designs, develops and maintains highly scalable, secure and reliable data structures. Accustomed to working closely with system architects, software architects and design analysts to understand business or industry requirements to develop comprehensive data models. Proficient at developing database architectural strategies at the modeling, design and implementation stages. Astute [Job Title] with data-driven and technology-focused approach. Communicates clearly with stakeholders and builds consensus around well-founded models. Talented in writing applications and reformulating models.

Analytical and solution-oriented Data Analyst/Data Engineer with over 5 years of experience designing, developing, and optimizing scalable data pipelines and analytical solutions across cloud and distributed environments, primarily on Microsoft Azure and Databricks. Proven ability to transform structured and unstructured data into actionable business insights through ETL/ELT processes, advanced data modeling, and real-time processing frameworks using PySpark, Scala, and SQL. Strong expertise in applying statistical analysis, data mining, and predictive modeling to uncover trends and support data-driven decision-making. Adept at leveraging tools like Azure Synapse, Delta Lake, Power BI, and Azure Data Factory to deliver measurable business value. Skilled in collaborating across multidisciplinary teams, with excellent communication and problem-solving abilities. Committed to continuous learning, automation, and innovation to improve performance and enable data maturity across organizations.

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.

Michael Staves

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Senior Data Engineer

Senior Technical Trainer

Network Administrator

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Bachelor of Science - Information Technology

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Senior Technical Trainer

Network Administrator

Bachelor of Science - Information Technology

Senior Data Engineer

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