- Pioneered the data architecture at Synapticure as the first data hire, establishing a unified data warehouse to centralize and analyze clinical and operational data, enhancing decision-making from the outset.- Implemented Apache Airflow on Kubernetes, designed a metadata tracking system, and developed an ETL framework to streamline data integration from multiple sources, ensuring research-grade data integrity and traceability.- Developed comprehensive clinical operations analytics, including dashboards for onboarding funnels, patient demographics, referral patterns, and provider utilization, aiding in strategic planning and operational efficiency.- Addressed revenue cycle management challenges by automating billing processes, eliminating a 20-hour weekly manual workload for the billing team, and improving accuracy in revenue reporting and claims management.- Collaborated with accounting to enhance financial understanding and reporting, facilitating more accurate revenue accrual, accounts receivable tracking, and payment allocation.- Contributed to product development by identifying business challenges, proposing solutions, and measuring the impact of implemented strategies, bridging data insights with product innovation.- Launched Synapticure's first Real World Data (RWD) product, delivering a web dashboard for analyzing patient outcomes and treatment patterns, driving data-driven decision-making in patient care.

- Developed Epic FHIR integration for telehealth clinic- Architected data platform for servicing real-time and batch data

- Joined Lark as a Senior Data Engineer, quickly adapting to a new technical environment by learning Scala and contributing to ETL processes and Airflow orchestration within the first few months.- Identified and resolved critical issues in the team's Scala environment and build process, leading to the development of a standardized build process using Scala Build Tool (sbt) and Makefile, significantly improving deployment reproducibility and efficiency.- Spearheaded the integration of ETL code with the DevOps team's continuous integration processes, laying the groundwork for continuous deployment with Airflow.- Played a pivotal role in the development of the data mart, collaborating with an expanded team of engineers, ensuring scalability on Spark, mentoring peers through pair-programming, and guiding architectural decisions.- Led a cross-functional project as the Data Engineering Lead, working closely with product management, project management, and application engineering teams to define data models and ensure smooth data source transitions in the data mart.- Initiated and led the development of a new data catalog API, transitioning from a bespoke DynamoDB solution to a REST API, enabling seamless access for both Scala and Python environments, and coding the API in Go for AWS Lambda.

- Transitioned from Principal Engineer to Data Infrastructure Manager, seamlessly adapting to leadership responsibilities while managing 4 direct reports and leading an extended team of 4 others, ensuring effective team collaboration and data delivery.- Played a pivotal role in working closely with downstream data consumers, ensuring their access to essential data and laying out a vision for scalable data operations to support the company's growth.- Led the management and optimization of ingesting over 1,000+ data streams, employing parquet partitions to update our unified data structure, enhancing data efficiency and accessibility.Initiated and executed strategies to shift downstream team operations from batch processing to real-time, event-driven ETL, enabling more frequent updates and increased data utility for internal consumers.- Collaborated with engineering and product teams to define a comprehensive roadmap for integrating external data sources, balancing new feature development, pipeline deployment, and data volume growth.- Engaged with clinical stakeholders to expand data normalization efforts, identifying valuable data sets, evaluating normalization challenges, and assessing impacts on downstream applications, driving enhanced data-driven decision-making capabilities.

Technical lead for development of end-to-end data ingestion platform to automate acquisition and unification of healthcare data sources leveraging AWS cloud-native hybrid serverless infrastructure.• Lead team of 3 developers creating remotely managed C# .Net application responsible for performing secure extraction and transfer of healthcare data.• Lead team of 4 AWS data engineers developing microservices based event driven data ingestion and normalization processes powered by internal web application for managing, orchestrating, and executing ETL for a variety of incoming data sources.• Coordinate with Production and Technology leadership to set scope, define roadmaps, and plan sprints and releases.• Guide engineers to promote code quality, implementing unit and integration testing, and develop maintainable software solutions.

Develop and deploy ETL processes and pipelines to facilitate data communications, management, and analysis of data from multiple large-scale sources. Leverage AWS with Lambda, RDS, Glue, Redshift, S3, Step Functions, and API Gateway to create and implement server-less ETL pipelines.• Implement flexible, scalable structures that resolve differences between health care data systems.• Build a system to manage source-to-target data definitions for over 3,000 future ingestion streams.• Develop and implement an event-driven ingestion architecture that automatically processes data as itlands in the production AWS environment.• Create system enhancements to expand ingestion pipelines to facilitate the rapid onboarding of newdata streams.• Design and implement a web UI for creating source-to-target data mapping with versioning.

Developed and implemented a data lake, performed data analysis, and coordinated the creation of ingestion pipelines for data sources required for business analysis processes. Collaborated with senior business leaders, including C-level executives, to identify data analysis requirements, and translate operational needs into creative, scalable data management solutions and Tableau dashboards.• Created systems that improved decision-making processes, working with business units to develop key performance indicators (KPIs) and aggregate data for business analysis efforts.• Engineered machine learning pipelines that powered a web application used to conduct financial risk management processes.• Leveraged multidisciplinary skills in software development to develop systems and enhancements, including ETL pipelines with Spark on a Hadoop/Hive stack, REST APIs for machine learning in web applications, creating reports, and implementing predictive models into an SQL database.• Developed a verification processes for data lake ingestion into production environments.• Held weekly meetings with division management to communicate best practices and actions to effectively utilize data insights to influence operational decisions.

Built data visualization dashboards that were used to communicate market opportunities to potential customers. Created an algorithm to compare market segments and use the results of internal surveys for decision-making processes.

I have been working with this company for many years providing many different services. I have been doing general construction, including: framing, roofing, trimming, tiling, flooring, cabinetry, and basic electrical & plumbing. I have been heavily involved in the building process from planning to selling and have gained various skills in my time working for this company that will continue to help me for he rest of my life.