April 2018 – October 2018

Category	Details
Project Role	SnapLogic Developer
Industry	Insurance Sector
Market	LATAM
Client Challenge	The client’s SQL database consisted of numerous disconnected tables lacking a relational structure or historical tracking. This fragmentation made consistent reporting and trend analysis impossible. Without visibility into how policy or customer data changed over time, business teams were forced to rely on manual, reactive decision-making rather than data-driven insights.
Responsibilities	My role was defined by the need to bridge the gap between fragmented data and actionable history. I was responsible for: – Defining and executing a data historization strategy to centralize disparate datasets. – Designing SnapLogic ETL pipelines capable of managing incremental data updates from multiple SQL sources. – Establishing data governance and auditability standards to ensure all historical tracking met reporting readiness requirements.
Technical Solution	To address the lack of visibility, I built a custom SCD Type 2 framework directly within SnapLogic. Instead of using external scripts, I embedded the historization logic into the pipelines themselves. I designed these pipelines to be parameterized and reusable, allowing them to automatically detect, insert, and update records while maintaining versioning and timestamps for every change. To ensure the system could handle large volumes without dragging down performance, I implemented Change Data Capture (CDC). This allowed me to process only the deltas (the actual changes) rather than scanning entire tables, which significantly minimized runtime and resource consumption. I then developed the target SCD Type 2 tables to serve as the persistent storage layer for these historical versions. For the final layer of the solution, I focused on maintainability. I integrated automated logging, error handling, and audit trails into the workflow. This provided a transparent record of every data movement, ensuring that any discrepancies could be traced and resolved quickly.
Outcome	By transforming disconnected SQL tables into a fully historized, report-ready data model, I enabled the client to produce comprehensive trend and historical analysis reports for the first time in their operations. This strategic shift from reactive to data-driven decision-making was supported by a significant reduction in technical debt and manual oversight. Key Project Metrics: – 25% Reduction in manual data maintenance efforts. – 35% Improvement in pipeline runtime through optimized delta processing. – 100% Visibility into historical policy and customer data changes.
Tech Stack	SnapLogic, Microsoft SQL Server, REST/SOAP Web Services

March 2019 – August 2019

Category	Details
Project Role	SnapLogic Developer
Industry	Finance
Market	North America
Client Challenge	The client relied on manual data exchanges between their internal systems and NetSuite, which caused frequent reconciliation errors and significantly delayed revenue reporting. These manual bottlenecks hindered the finance team’s ability to provide timely and accurate financial insights.
Responsibilities	My remit for this project was to lead the transition from manual processes to a fully automated integration architecture. I was specifically tasked to: – Serve as the primary technical point of contact for both the SnapLogic and NetSuite workstreams. – Partner with finance stakeholders to map complex business logic into reliable, automated integration flows. – Direct the environment deployment and version control strategy to ensure consistent code promotion between Dev, Test, and Production environments. – Coordinate User Acceptance Testing (UAT) and work directly with end-users to validate data quality and business logic.
Technical Solution	To automate the full order-to-cash cycle, I delivered a comprehensive SnapLogic-based API integration framework. I leveraged REST and Web Services Snaps to establish real-time synchronization with NetSuite, ensuring that data flowed seamlessly between systems without manual intervention. The core of the architecture involved specialized SnapLogic ETL pipelines designed for data extraction, enrichment, and transformation. This ensured high record accuracy before final loading. To improve long-term maintainability, I developed modular, reusable sub-pipelines for high-frequency financial operations like order posting and invoice creation. I also managed the NetSuite configuration side, including custom fields, mappings, and validation scripts. To ensure the system was robust, I integrated transaction-level traceability through custom error-handling, logging, and automated alerting mechanisms.
Outcome	The project successfully eliminated the client’s reliance on semi-manual data exchanges by achieving 100% automation of Sales Order, Invoice, and Credit Memo synchronization. By removing these manual bottlenecks, the finance team saved several hours of daily processing time, while the business gained a robust foundation for future cross-system data enhancements. Key Project Metrics: – 60%+ Reduction in reconciliation errors, leading to more accurate financial reporting. – 35% Improvement in transaction throughput via Snap optimization and parallel processing. – 100% Automation of the critical order-to-cash synchronization cycle.
Tech Stack	SnapLogic, NetSuite, REST Web Services

August 2019 – December 2021

Category	Details
Project Role	Team lead & SnapLogic Developer
Industry	Telecommunications
Market	North America
Client Challenge	The client’s Business Intelligence department needed to streamline how operational data was replicated, stored, and prepared for reporting. While data was landing in Redshift via Attunity, the environment lacked the automation and visibility required for accurate, timely decision-making.
Responsibilities	Leading this initiative required me to oversee the end-to-end modernization of the data lifecycle. I was responsible for: – Managing a technical team of four (developers and DevOps) to deliver on BI department goals. – Defining the integration architecture and development standards for all data flows. – Orchestrating the migration of data pipelines from Redshift to Snowflake, focusing on performance and cost. – Designing the SnapLogic pipelines used for ingestion, transformation, and delivery to Tableau. – Governing environment deployments and operational monitoring in collaboration with the infrastructure teams.
Technical Solution	I developed a modular SnapLogic framework to automate the entire analytics lifecycle, starting with data ingested from Attunity into Redshift. As the project progressed, we successfully transitioned these processes to Snowflake to improve scalability. We built these pipelines to be parameterized and reusable, which allowed us to transform and distribute data to Tableau reporting layers with much higher consistency. To ensure the system was robust, we implemented advanced error handling and monitoring that provided full traceability for every process. We also enabled incremental data loading and optimized scheduling, which shifted the client from daily batch processing to near-real-time analytics. On the operational side, I worked closely with DevOps to automate our version control and deployment pipelines, ensuring that updates were promoted smoothly across all environments.
Outcome	I successfully delivered a fully automated BI data flow and migrated the environment from Redshift to Snowflake without any operational disruption. Key Project Metrics: – Refresh time reduced from several hours to under 30 minutes per cycle. – 50% Improvement in reporting accuracy and timeliness. – Seamless migration to Snowflake with zero downtime for business users.
Tech Stack	SnapLogic, Snowflake, Redshift, SFTP, Web Services REST/SOAP, Attunity

December 2021 – September 2022

Category	Details
Project Role	SnapLogic Consultant
Industry	Telecommunications
Market	Global
Client Challenge	The client maintained a massive integration landscape burdened by years of technical debt from legacy ETL tools and complex XSLT-based transformations. Over time, multiple teams had layered scripts that made the environment slow, expensive to maintain, and difficult to scale. The objective was to migrate these mission-critical integrations to SnapLogic, prioritizing business continuity while refactoring the logic for better performance.
Responsibilities	In this consulting engagement, I was tasked with orchestrating a complete platform modernization while ensuring no disruption to global operations. My key mandates were to: – Establish the overarching migration framework and strategy for transitioning legacy assets to SnapLogic. – Accelerate the delivery timeline by identifying opportunities to reuse existing XSLT schemas during the initial phase to maintain continuity. – Direct the optimization efforts in the second phase to replace legacy logic with high-performance, native SnapLogic components. – Align cross-functional workflows between Kafka and ServiceNow teams to enhance operational visibility and event-driven data flows. – Uphold technical standards through consistent code reviews, mentoring of team members, and deep-dive performance audits.
Technical Solution	To manage the scale of this migration, I developed a two-phase framework that balanced immediate stability with future-proof modernization. Phase 1: I focused on speed and continuity by building a specialized migration utility layer. This allowed me to wrap the existing XSLT transformations directly within SnapLogic pipelines, achieving functional equivalence with the legacy system without requiring an immediate rewrite of the underlying business logic. Phase 2: Once the integrations were stable on the new platform, I moved into a full refactoring effort. I leveraged SnapLogic-native mappers, JSON/XML processing, and modular sub-pipelines to replace the heavy legacy code, which drastically reduced technical debt and increased throughput. I also implemented parameterized pipelines and a centralized error-handling framework to ensure the system was both transparent and easy to maintain. To support real-time requirements, I integrated SnapLogic with Kafka for asynchronous event handling and ServiceNow for automated incident tracking. This ensured that the support teams had immediate visibility into any issues, significantly improving operational uptime.
Outcome	I successfully transitioned over 80 legacy integrations to SnapLogic with zero data loss or system downtime, delivering a reusable migration framework that was eventually adopted for all other system migrations within the company. Key Project Metrics: – 80+ Legacy Integrations successfully migrated. – 45–50% Performance boost achieved in refactored and optimized pipelines. – 40% Reduction in initial migration effort by reusing ~70% of legacy XSLT logic in Phase 1. – Significant Decrease in ongoing maintenance costs through native refactoring.
Tech Stack	SnapLogic, Kafka, XSLT, Web Services

October 2022 – July 2025

Category	Details
Project Role	SnapLogic Architect
Industry	Banking
Market	UK
Client Challenge	A major UK bank required a high-security integration platform to serve as the central middleware for sensitive customer and financial data across core banking and CRM systems. The primary challenge was to architect a system that met rigid UK banking regulations—specifically regarding data accuracy, auditability, and segregation of duties—without compromising on the high-performance demands of financial transaction processing.
Responsibilities	For this multi-year engagement, I was charged with the architectural leadership and delivery of a mission-critical integration platform. My mandate included: – Leading a technical team of three SnapLogic developers while coordinating with cross-functional Security, QA, Infrastructure, and Architecture units. – Architecting secure data flows to handle SWIFT MT and MX payment files, JMS queue messaging, and SFTP transfers. – Defining a formal CI/CD strategy and version control framework using GitHub to govern and automate environment promotions. – Representing the SnapLogic team on-site in London during the go-live phase to ensure a stable production transition after three years of development.
Technical Solution	To meet the bank’s stringent security requirements, I designed the SnapLogic ecosystem with a “compliance-first” philosophy. I began by introducing a library of shared components for transformation logic, encryption, and credential management. This ensured that every pipeline followed the same security protocols and made the system significantly easier to audit. To provide the necessary traceability, I implemented a centralized logging and audit tracking framework across the entire architecture, allowing for end-to-end visibility of every financial record. Connectivity was handled through a hybrid messaging approach. I integrated AWS SQS for asynchronous message exchanges and JMS queues for internal event-driven processing, ensuring that the bank could handle fluctuating transaction volumes reliably. For payment file transfers, I built secure SFTP-based interfaces specifically tailored to handle the complexities of SWIFT MT/MX formats. Throughout the build, I applied rigorous data validation and encryption mechanisms to align with UK regulatory and internal audit policies. To maintain code integrity across the long development lifecycle, I established a deployment governance model using GitHub workflows, which allowed for controlled, peer-reviewed environment promotion.
Outcome	I delivered a fully regulated, audit-ready architecture that now serves as the strategic middleware for the bank’s mission-critical integrations and future automation initiatives. Key Project Metrics: – >99.5% Process Reliability achieved with zero data loss in a production environment. – 45% Reduction in integration development time through the use of standardized design patterns and reusable components. – Successful on-site delivery and production stability following the high-stakes London go-live.
Tech Stack	SnapLogic, JMS Queues, SFTP, SWIFT MT/MX, GitHub

January 2024 – January 2025

Category	Details
Project Role	SnapLogic Integration Lead
Industry	Chemicals / Manufacturing
Market	North America
Client Challenge	The client operated with a highly fragmented data landscape where critical business information was siloed across aging, disconnected systems—including legacy Microsoft Access databases. This lack of a centralized repository made enterprise-wide data analysis impossible. The organization needed to move these disparate datasets into a modern, unified data warehouse to enable advanced analytics, but the migration had to happen without disrupting ongoing operations.
Responsibilities	My objectives for this large-scale migration were centered on the efficient extraction and consolidation of legacy data into the new enterprise warehouse. I was specifically responsible for: – Collaborating with the lead project architect to design an integration framework that aligned with the broader data warehouse strategy. – Designing and implementing high-volume SnapLogic pipelines in parallel to ensure the initial data load for the warehouse was completed within aggressive timelines. – Coordinating the systematic decommissioning of legacy databases, ensuring that data integrity was maintained as we transitioned away from each old system. – Partnering with the data engineering team to map complex source-to-target requirements and ensure the landing zones met the warehouse specifications.
Technical Solution	To handle the scale and complexity of this migration, I developed the integration layer using a microservices-based architecture within SnapLogic. Rather than building massive, rigid pipelines, I created modular, task-specific integrations that were easier to scale, test, and deploy. This allowed me to trigger multiple extraction processes in parallel, which was critical for the first phase of the project: the mass ingestion of data from the legacy Access and SQL systems into the new warehouse. The project was executed in two distinct phases. In the first phase, I focused on building out the parallel infrastructure to “feed” the warehouse. I implemented robust validation logic to ensure that data from the old systems was cleaned and transformed correctly before being stored. In the second phase, I led the transition effort to retire the legacy databases. By adopting a “system-by-system” approach, I managed the cut-over for each individual database, ensuring that all dependent processes were successfully re-routed to the new warehouse before the old systems were powered down.
Outcome	I successfully led the integration workstream that populated the client’s first centralized data warehouse, enabling the complete retirement of their legacy database infrastructure. Key Project Metrics: – 100% Migration of critical legacy datasets into the new enterprise data warehouse. – Successful Decommissioning of all target legacy systems, including fragmented MS Access databases, with zero loss of historical data. – Parallel Execution Strategy reduced initial data loading time by approximately 40% compared to sequential processing.
Tech Stack	SnapLogic, MS Access, SQL Server, Enterprise Data Warehouse (EDW)

September 2025 – Current

Category	Details
Project Role	Senior Boomi Consultant
Industry	Non-Profit / Charitable Sector
Market	Global
Client Challenge	The client operates a complex, global integration landscape built on a cluster setup with numerous legacy processes that have become difficult to manage. Many of these inherited integrations were not originally designed for modern scalability, leading to reliability issues and a lack of clear visibility into data health. The primary objective is to move away from these “black box” legacy systems toward a transparent, high-performance architecture that can support the organization’s long-term humanitarian goals.
Responsibilities	I am tasked with providing the strategic and architectural leadership required to modernize the client’s integration ecosystem. My responsibilities include: – Leading all technical initiatives and defining the long-term roadmap for the Boomi environment. – Managing stakeholder relationships, acting as the primary bridge between business leadership and the technical delivery team. – Collaborating closely with a Boomi developer to translate architectural designs into functional, high-quality integrations. – Advising on and designing structural improvements to resolve existing technical debt and improve system maintainability. – Planning and governing the future workload, ensuring that development resources are aligned with the most critical organizational priorities.
Technical Solution	The core of the solution I am implementing is a transition from rigid, batch-heavy legacy processes to a modern, event-driven architecture. To achieve this, I am leading the redesign of our integration patterns to utilize Event Streams, allowing for real-time data movement and significantly better performance across their global network. To address the client’s lack of visibility, I am overseeing the implementation of a centralized observability layer. Instead of relying on Boomi’s internal logs, we are streaming execution data and metadata into a third-party database. This data is then visualized through Power BI dashboards, which I designed to provide stakeholders with their first comprehensive view of integration health and business-critical metrics. On the connectivity side, I work with the development team to standardize how we interface with core systems like Dynamics 365. By moving away from poorly documented legacy integrations and implementing standardized Web Services and SFTP patterns, we are building a more resilient framework that is easier to troubleshoot and scale as the organization’s needs evolve.
Outcome	I have established a disciplined, architecturally sound development cycle that provides the client with both operational stability and a clear path toward total system modernization. Key Project Metrics: – Established a strategic roadmap for the modernization of 100% of high-risk legacy integrations. – Improved operational visibility through the delivery of a real-time Power BI-based monitoring suite. – Reduced system latency by shifting core processes to an event-driven model.
Tech Stack	Dell Boomi, Dynamics 365, Event Streams, Power BI, SQL, SFTP, Web Services (REST/SOAP)