Snr. Data Engineering Consultant at YK Consulting
Florida, United States
Yegor
Koriagin
Council Member
Yegor Koriagin is a Senior Data Engineer and Architect with over 14 years of experience across financial services, private equity, management consulting, healthcare, and technology. The majority of his career has focused on designing and delivering cloud-native data platforms, with the last six or more years dedicated to independent consulting, helping global startups and mid-sized companies implement modern data warehousing and data processing environments.
Yegor Koriagin currently serves as Data Architect at Arizent, a role he has held since December 2020. In this position, he led a comprehensive redesign of the company's data platform, beginning with a thorough analysis of the existing architecture and moving through to a future-state design aligned with modern best practices in scalability, security, and GDPR compliance. He re-engineered data pipelines and introduced modern ELT frameworks, reducing manual data handling by 50% across the full ETL lifecycle. He built the consolidated BI layer aggregating data from sources including Salesforce, Piano, Zeta, Bizzabo, SimilarWeb, and SocialFlow, and developed the integration strategy for Salesforce and related modules such as Zuora, automating process flows and opportunity management. He designed reusable data models supporting enterprise-wide BI and data science initiatives, built out marketing and sales analytics covering subscription analytics, funnel analytics, social media, campaign performance, content, and audience data, and defined the long-term roadmap for those functions. He served as the connector between marketing, sales, C-level leadership, and the data analytics team, translating business requirements into technical solutions. He also mentored junior team members, led hiring for the data engineering and architecture function, and maintained the internal knowledge base across architectural decisions and data standards. The platform runs on GCP infrastructure with BigQuery, Cloud Storage, Cloud Functions, and Matillion ETL.
Concurrently, from October 2022 to June 2023, Yegor Koriagin worked as Data Architect and DBA at Triumphtech, an AWS Premier Tier services provider. There he led the migration of a Google BigQuery-based data warehouse to Snowflake on AWS, defining the end-to-end migration strategy, designing the target-state architecture with an emphasis on scalability and cost-efficiency, and executing data migration plans with comprehensive validation to ensure data integrity. He also migrated and reconfigured downstream dependencies including Prefect-managed data flows and Looker BI dashboards, and delivered consulting on data modeling and solution architecture for an AI chatbot platform, focusing on scalable data structures and real-time integration. The engagement used Snowflake, dbt, Prefect, Looker, Airbyte, BigQuery, and AWS and GCP infrastructure.
Yegor Koriagin has run an independent data engineering consultancy from 2020 through 2025, delivering full-scale data platform engagements across manufacturing, wealth management, solar energy, HR, education, finance, and e-commerce clients. For a manufacturing firm in 2025, he led the design of a Databricks-based data lake on Azure for multi-source integration from on-premises systems including BC14, SharePoint, Teams, and internal product databases. He built out medallion architecture layers, implemented data governance and security with Azure Purview, developed and optimized PySpark code, and organized a vector store in the gold layer for AI agent consumption using Mosaic Vector Store and Mosaic Endpoints, while defining the AI integration architecture with LangChain and Azure OpenAI services. For a wealth management firm from 2024 to 2025, he re-engineered legacy SSIS ETL processes onto Azure Databricks, improving scalability and reducing processing time in the cloud, and established data quality, resiliency, and governance procedures across the pipeline. For a solar energy firm over the same period, he replaced a legacy Excel-based reporting environment with a modern Microsoft Fabric platform, building end-to-end ingestion pipelines from Microsoft Dynamics, HubSpot, planning tools, and Excel files into structured Bronze, Silver, and Gold data layers. He designed analytics-ready star schemas with Slowly Changing Dimensions, built Power BI semantic models with standardized KPI definitions, and implemented role-based access control across business units including Finance, Operations, Sales, and Leadership, eliminating manual reconciliation and multiple conflicting versions of reports. For a data anonymization platform, he designed and deployed Informatica Cloud Data Integration pipelines ingesting data into Snowflake and built Application Integration workflows to orchestrate anonymization processes via REST APIs, ensuring PII and financial data were properly masked for downstream analytics. Across earlier cloud data warehouse engagements from 2020 to 2024, he designed and deployed solutions on Amazon Redshift and Google BigQuery, built ETL pipelines using Fivetran, Airbyte, Matillion, Stitch, and AWS Glue, implemented orchestration with Apache Airflow, Dagster, and Prefect, and built large-scale distributed processing jobs in Java with Apache Spark on AWS EMR over multi-terabyte datasets.
Yegor Koriagin currently serves as Data Architect at Arizent, a role he has held since December 2020. In this position, he led a comprehensive redesign of the company's data platform, beginning with a thorough analysis of the existing architecture and moving through to a future-state design aligned with modern best practices in scalability, security, and GDPR compliance. He re-engineered data pipelines and introduced modern ELT frameworks, reducing manual data handling by 50% across the full ETL lifecycle. He built the consolidated BI layer aggregating data from sources including Salesforce, Piano, Zeta, Bizzabo, SimilarWeb, and SocialFlow, and developed the integration strategy for Salesforce and related modules such as Zuora, automating process flows and opportunity management. He designed reusable data models supporting enterprise-wide BI and data science initiatives, built out marketing and sales analytics covering subscription analytics, funnel analytics, social media, campaign performance, content, and audience data, and defined the long-term roadmap for those functions. He served as the connector between marketing, sales, C-level leadership, and the data analytics team, translating business requirements into technical solutions. He also mentored junior team members, led hiring for the data engineering and architecture function, and maintained the internal knowledge base across architectural decisions and data standards. The platform runs on GCP infrastructure with BigQuery, Cloud Storage, Cloud Functions, and Matillion ETL.
Concurrently, from October 2022 to June 2023, Yegor Koriagin worked as Data Architect and DBA at Triumphtech, an AWS Premier Tier services provider. There he led the migration of a Google BigQuery-based data warehouse to Snowflake on AWS, defining the end-to-end migration strategy, designing the target-state architecture with an emphasis on scalability and cost-efficiency, and executing data migration plans with comprehensive validation to ensure data integrity. He also migrated and reconfigured downstream dependencies including Prefect-managed data flows and Looker BI dashboards, and delivered consulting on data modeling and solution architecture for an AI chatbot platform, focusing on scalable data structures and real-time integration. The engagement used Snowflake, dbt, Prefect, Looker, Airbyte, BigQuery, and AWS and GCP infrastructure.
Yegor Koriagin has run an independent data engineering consultancy from 2020 through 2025, delivering full-scale data platform engagements across manufacturing, wealth management, solar energy, HR, education, finance, and e-commerce clients. For a manufacturing firm in 2025, he led the design of a Databricks-based data lake on Azure for multi-source integration from on-premises systems including BC14, SharePoint, Teams, and internal product databases. He built out medallion architecture layers, implemented data governance and security with Azure Purview, developed and optimized PySpark code, and organized a vector store in the gold layer for AI agent consumption using Mosaic Vector Store and Mosaic Endpoints, while defining the AI integration architecture with LangChain and Azure OpenAI services. For a wealth management firm from 2024 to 2025, he re-engineered legacy SSIS ETL processes onto Azure Databricks, improving scalability and reducing processing time in the cloud, and established data quality, resiliency, and governance procedures across the pipeline. For a solar energy firm over the same period, he replaced a legacy Excel-based reporting environment with a modern Microsoft Fabric platform, building end-to-end ingestion pipelines from Microsoft Dynamics, HubSpot, planning tools, and Excel files into structured Bronze, Silver, and Gold data layers. He designed analytics-ready star schemas with Slowly Changing Dimensions, built Power BI semantic models with standardized KPI definitions, and implemented role-based access control across business units including Finance, Operations, Sales, and Leadership, eliminating manual reconciliation and multiple conflicting versions of reports. For a data anonymization platform, he designed and deployed Informatica Cloud Data Integration pipelines ingesting data into Snowflake and built Application Integration workflows to orchestrate anonymization processes via REST APIs, ensuring PII and financial data were properly masked for downstream analytics. Across earlier cloud data warehouse engagements from 2020 to 2024, he designed and deployed solutions on Amazon Redshift and Google BigQuery, built ETL pipelines using Fivetran, Airbyte, Matillion, Stitch, and AWS Glue, implemented orchestration with Apache Airflow, Dagster, and Prefect, and built large-scale distributed processing jobs in Java with Apache Spark on AWS EMR over multi-terabyte datasets.
From May to October 2021, Yegor Koriagin was Senior Data Warehouse Engineer at Tblue, where he designed and developed a PostgreSQL-based data warehouse from scratch on AWS, built a custom ETL framework using AWS Lambda and PostgreSQL functions, and established a data quality framework to monitor and validate daily data loads.
From November 2020 to May 2021, Yegor Koriagin worked as Senior Data Engineer at Advent International, contributing to an internal platform that consolidated data on public companies into a centralized PostgreSQL database to support investment decision-making. He integrated approximately 20 external data sources, designed the PostgreSQL data models, built and maintained the ETL pipelines, and led code reviews and mentoring to raise development standards across the team.
From July 2017 to October 2020, Yegor Koriagin served as Senior DBA and Technical Lead at SoftServe, where he led the cloud migration of an on-premises infrastructure to AWS for a top-tier management consulting client. The environment comprised over 100 Windows-based servers and more than 50 TB of data. He defined the migration strategy, executed SQL Server migrations using AWS Snowball for bulk transfer followed by differential backup syncing for near-zero downtime, migrated data warehouse and ETL processes from SQL Server and SSIS to Snowflake, converted SAS workflows and ML algorithms to Python and TensorFlow, and performed deep post-migration performance tuning across SQL Server instances. During an engagement at Qubole from October 2018 to February 2019, he conducted a hands-on competitive assessment of major big data platforms including AWS EMR, Azure HDInsight, Databricks, and Qubole, defining evaluation criteria and scoring models across performance, scalability, cost-efficiency, and operational complexity, and delivering comparative analysis to guide strategic platform selection. From May 2018 to February 2019, he worked as Solutions Data Architect on a Nike engagement, participating in the proposal, design, and implementation of a centralized data warehousing solution on AWS with Snowflake and S3, developing the integration strategy for near real-time synchronization from Nike's legacy DB2 systems, and providing technical guidance across both POC and full implementation phases. From July 2017 to April 2019, he also served as Data Architect at Goodiebox, leading the end-to-end development of a GCP-based analytics platform from the ground up, implementing ETL pipelines for approximately 10 marketing platforms, building the full BI layer with master data mapping and reporting structures, and reporting directly to the CEO on platform performance and business impact.
From June 2016 to July 2017, Yegor Koriagin was Senior PostgreSQL and Redshift DBA at SoftServe, working on a healthcare product. He designed Redshift clusters and reporting tables, tuned queries to reduce response times from several minutes to milliseconds, implemented a real-time analytics solution using Redshift, PostgreSQL, and Kinesis, and delivered High Availability strategies for PostgreSQL including streaming replication and failover mechanisms.
Earlier in his career, Yegor Koriagin worked as an independent consultant from October 2015 to June 2016, building PostgreSQL-based systems on AWS for HR and other clients, converting Hadoop-based batch reporting to real-time systems, and rewriting Spark and Java-based logic into PostgreSQL views. From December 2014 to November 2015, he worked as PL/SQL Developer and Consultant at Miratech on behalf of Lindorff AS, leading the migration from Powerhouse to Oracle PL/SQL and Informatica, developing and optimizing ETL workflows in Informatica PowerCenter, and managing source control and deployment processes using SVN. From February to June 2014, he was an Oracle Developer at Luxoft on an offshore team supporting Deutsche Bank, designing and optimizing Informatica ETL
From November 2020 to May 2021, Yegor Koriagin worked as Senior Data Engineer at Advent International, contributing to an internal platform that consolidated data on public companies into a centralized PostgreSQL database to support investment decision-making. He integrated approximately 20 external data sources, designed the PostgreSQL data models, built and maintained the ETL pipelines, and led code reviews and mentoring to raise development standards across the team.
From July 2017 to October 2020, Yegor Koriagin served as Senior DBA and Technical Lead at SoftServe, where he led the cloud migration of an on-premises infrastructure to AWS for a top-tier management consulting client. The environment comprised over 100 Windows-based servers and more than 50 TB of data. He defined the migration strategy, executed SQL Server migrations using AWS Snowball for bulk transfer followed by differential backup syncing for near-zero downtime, migrated data warehouse and ETL processes from SQL Server and SSIS to Snowflake, converted SAS workflows and ML algorithms to Python and TensorFlow, and performed deep post-migration performance tuning across SQL Server instances. During an engagement at Qubole from October 2018 to February 2019, he conducted a hands-on competitive assessment of major big data platforms including AWS EMR, Azure HDInsight, Databricks, and Qubole, defining evaluation criteria and scoring models across performance, scalability, cost-efficiency, and operational complexity, and delivering comparative analysis to guide strategic platform selection. From May 2018 to February 2019, he worked as Solutions Data Architect on a Nike engagement, participating in the proposal, design, and implementation of a centralized data warehousing solution on AWS with Snowflake and S3, developing the integration strategy for near real-time synchronization from Nike's legacy DB2 systems, and providing technical guidance across both POC and full implementation phases. From July 2017 to April 2019, he also served as Data Architect at Goodiebox, leading the end-to-end development of a GCP-based analytics platform from the ground up, implementing ETL pipelines for approximately 10 marketing platforms, building the full BI layer with master data mapping and reporting structures, and reporting directly to the CEO on platform performance and business impact.
From June 2016 to July 2017, Yegor Koriagin was Senior PostgreSQL and Redshift DBA at SoftServe, working on a healthcare product. He designed Redshift clusters and reporting tables, tuned queries to reduce response times from several minutes to milliseconds, implemented a real-time analytics solution using Redshift, PostgreSQL, and Kinesis, and delivered High Availability strategies for PostgreSQL including streaming replication and failover mechanisms.
Earlier in his career, Yegor Koriagin worked as an independent consultant from October 2015 to June 2016, building PostgreSQL-based systems on AWS for HR and other clients, converting Hadoop-based batch reporting to real-time systems, and rewriting Spark and Java-based logic into PostgreSQL views. From December 2014 to November 2015, he worked as PL/SQL Developer and Consultant at Miratech on behalf of Lindorff AS, leading the migration from Powerhouse to Oracle PL/SQL and Informatica, developing and optimizing ETL workflows in Informatica PowerCenter, and managing source control and deployment processes using SVN. From February to June 2014, he was an Oracle Developer at Luxoft on an offshore team supporting Deutsche Bank, designing and optimizing Informatica ETL