Healthcare Outcomes Performance Co. (HOPCo)

As Lead Data Engineer for myrecovery (a HOPCo digital product), I’m responsible for scaling and optimising our Snowflake data infrastructure. I lead initiatives to streamline and enhance data workflows, improve documentation, and ensure our platform supports secure, efficient, and scalable analytics to power better patient care and outcomes.

Lead Data Engineer

CAI Parsable

At CAI Parsable, I engineered and implemented a robust AWS data Lakehouse at CAI Parsable, optimizing the ingestion and processing of Change Data Capture (CDC) data from a transactional Postgres database.

•	Architected an efficient data pipeline using AWS DMS to land RDS Postgres CDC data into S3, then leveraged dbt and Athena to ingest and structure data into Apache Iceberg tables.
•	Successfully integrated the Lakehouse as a central source for data products, achieving notable cost savings and significantly reducing the complexity of data maintenance.
•	Improved observability and monitoring of data product health through the implementation of Datadog.
•	Managed and automated the provisioning of essential AWS infrastructure (S3 buckets, DMS instances, ECS Fargate Tasks, AWS Quicksight Datasets, IAM Roles) using Terraform for consistency and reliability.

Tech stack: AWS (Database Migration Service (DMS), S3, Glue, Athena + Apache Iceberg, ECS Fargate, DynamoDB), dbt, GitHub + GitHub Actions for CI/CD, Terraform, Python, DataDog

Staff Data Engineer

Antonison Consulting Group

Delivered Data Engineering and Architecture solutions at Antonison Consulting Group that enabled client growth and enhanced operational efficiency.

•	Univ. of Florida Bowden Lab (www.bowdenlaboratory.com) - February 2023 to December 2023
    -	Worked with a PhD Student to streamline the processing and management of Mass Spectrometry data. https://github.com/alex-antonison/PFAS-Automated-Quantitation

•	MTSU Data Science Institute (https://mtsu.edu/datascience/) - November 2021 to August 2023
    -	Acted as an in-house technical expert for building scalable cloud data applications in support of research and education outreach initiatives.  Built a data platform to ingest raw data files into a data lake, process into a data warehouse, and serve up results for users within the Environmental Protection Agency.
    -	Built a serverless data lake using AWS S3, Glue, Lambda, and Step Functions for pre-processing the raw sensor and metadata files into a staging location in S3.
    -	Used Athena and dbt run via a Serverless Fargate Task to process the data into a normalized data warehouse and marts.
    -	Built data marts to serve data via dashboards in AWS Quicksight.

•	Concert Genetics (https://www.concertgenetics.com/) - February 2022 to March 2022  
    -	Conducted an assessment and provided actionable improvements in the realms of Data Infrastructure, Data Management, and Data Analytics workflow.

•	Verana Health (https://www.veranahealth.com/) - November 2021 to March 2022 
    -	Advised Verana Health as a Data Solutions Consultant on the architecture and development of a large-scale data lake to ingest data from thousands of EHR systems for their Real World Evidence repositories.

•	Picknic (https://picknic.app/) - June 2020
    -	Assessed the client's existing data ingestion architecture and processes for the Picknic application; advised on industry best practices to streamline data ingestion and improve data management.

Data Solutions Consultant

Nashville Data Nerds

When I took over Nashville Data Nerds, I built the meetup to be around promoting education with working with data. We met monthly where I would bring in conversation leaders to lead conversations around various topics such as skills necessary to be a successful Data Scientist to fairness and bias in AI. After a bit over 3 years, I decided to step down as the organizer and handed the reins over and am happy to see the meetup is better than ever! I recommend checking out all of the events they have going on at https://www.meetup.com/data-nerds/

Community Organizer

Verana Health

Developed a data ingestion platform at Verana Health to extract data from diverse Electronic Health Record (EHR) systems and transform it into a common data model, enabling standardized downstream processing and analysis.

•	Used AWS's Deequ library with PySpark to manage data profiling and quality as data flowed through ingestion pipelines.
•	Built AWS Glue PySpark jobs that ingested incremental data pulls into a staged data layer orchestrated by AWS Step Functions.
•	Developed application templates using cookiecutter that provided a standardized method of creating AWS Glue Jobs and Serverless Applications.  Templates included code for unit testing, generating fake data, and CI/CD configuration files for GitHub Actions.

Tech Stack: AWS (S3, Lambda, ECR/ECS/Fargate, Step Functions, Athena, Glue), Python, Serverless, GitHub

Data Engineer

Stratasan

Cast the technical vision for Data Engineering and Data Science at Stratasan, architecting optimal strategies for managing and scaling data products delivered through both Stratasan's custom application and Tableau.

•	Oversaw the Migration of a data pipeline built with Python and SQL run in Redshift with scaling issues to be rebuilt with dbt and Snowflake. This reduced the run time from days to hours.
•	Supported Stratasan's Tableau instance and provided support to analysts building data products.

Tech Stack: AWS (S3, EC2), Postgres, Redshift, Snowflake, Tableau, Luigi, SQL, Python, Bash, R, data-build-tool (dbt)

Principal Data Engineer

As Data Services Manager at Stratasan, directed the technical vision for Data Engineering and Data Science while mentoring and developing a team of data engineers and scientists. Established streamlined communication channels and intake processes to optimize workflow and project execution for the Data Services team.

•	Worked closely with the Product team to provide technical guidance on enhancing and developing new data products.
•	Implemented a reference data management process that improved control and communication around reference data sets.
•	Provided technical guidance on how to scale data products. This involved identifying new technologies, optimizing data, and automating manual data processes.

Manager of Data Services

axialHealthcare

Drove initiatives to streamline the deployment of models and analyses for the Data Science team. Accomplishments include implementing a specialized data science development strategy, creating an R package to standardize functions, and deploying a unified Redshift datastore. Concurrently, led the ongoing development and enhancement of models focused on optimizing clinical outreach.

•	Improved model and analysis development efficiency by developing and maintaining in-house R and python packages to streamline development actions and feature development. 
•	Improved the deployment of models from development to production by putting in place a source control strategy, environment management, and adding error handling and logging to models.
•	Provided development guidance related to coding practices and source control to fellow data scientists and researchers.
•	Reduced development downtime by ensuring compute resources for the data science team are operating nominally. This includes R Studio Server Pro, JupyterHub, and a Redshift cluster.

Tech Stack: AWS CLI, S3, Postgres, Redshift, Google Big Query, Google Cloud Storage, gsutil, SQL, Python, Bash, R

Machine Learning Engineer

At Axial Healthcare, a startup devoted to combating the opioid epidemic, I contributed to the Data Integration team by enhancing and managing the intake processes for critical client and reference data.

•	Improved client intake process of client data (Medical Claims, Rx Claims, Provider and Member information) by automating aspects of it.
•	Contributed to the development of an enhanced metric engine by coding the data extraction layer in Scala with Spark. 

Tech Stack: AWS CLI, S3, Hive, Presto, Athena, Postgres, Google Big Query, Google Cloud Storage, gsutil, SQL, Talend, Python, Bash, Scala, Spark
Operating Systems: Linux (Ubuntu), MacOS

Fresenius Medical Care North America

At FreseniusRx, a specialty pharmacy supporting End Stage Renal Disease (ESRD) dialysis patients, I enabled various analytic groups and day-to-day operations by developing robust data pipelines, managing data warehousing solutions, and creating and maintaining insightful reporting and dashboard tools.

•	Improved the quality and speed of delivering data and reports to the business by developing scheduled data pipelines using Talend that ETLed application and third-party data into a data warehouse.
•	Increased users' ability to access and utilize data by curating data marts and supporting self-service analytics with PowerBI and Excel (PowerQuery and PowerPivot)
•	Improved visibility into operational and compliance issues by developing automated report alerts that e-mailed stakeholders using SSRS and Talend.
•	Streamlined the extraction and loading of data into Salesforce using Talend in support of call center operations.

Data Environments: SQL Server 2012, Salesforce.com
Tech Stack: TSQL, Talend, Python, R, Excel 2013 (PowerPivot/PowerQuery/PowerMap), PowerBI, SSRS, JIRA, Confluence, BitBucket

Oilfield Instrumentation

Worked in the engineering department of an oilfield drilling instrumentation company and was responsible for supporting software development and client facing products.

* Improved the maintainability and efficiency of customer SSRS report suite.
Accomplished this by optimizing the underlying SQL.
* Supported software development by documenting and replicating software
bugs or feature issues. Would additionally collect changes to business logic if
necessary.
* Interacted with customers to assess possible software issues and provide
technical support.

Data Environments: Microsoft SQL Server (Enterprise - SQL Server 2012)
Operating Systems: Windows 8, Windows Server 2012
Tools: TSQL, SSRS, PowerShell, Team Foundation Server

Data Analyst

KBR Careers - Gov Solutions

Worked as a Data Engineer and Data Analyst in support of the PATRIOT System Effectiveness Model (PSEM), a simulation model of the PATRIOT missile defense system.

* Reduced the time of producing a comprehensive evaluation of PSEM’s
performance in integrated test events from days to a few hours. Accomplished
this with a series of shell scripts that loaded data into the database to queries
that processed and analyzed the results.
* Improved quality of new simulation model by helping design the new data
architecture.
* Helped improve software development efficieny by developing BASH shell
scripts that automated running software test suite and simulation test cases.
* Performed Verification and Validation activities on PSEM, co-authored reports
on the findings, and presented results to PATRIOT project office.

Data Environments: SQL Server 2008R2, SQL Server 2012, MySQL
Operating Systems: Linux (Red Hat), Windows 7
Tools: TSQL, Bash, C#, Excel

Data Engineer with 10+ years of experience delivering data-driven solutions across Government, Healthcare, and Environmental Science. I take a data product-oriented approach, working closely with stakeholders to define clear use cases and build solutions that drive meaningful outcomes. With a strong technical foundation, I can design and implement scalable data platforms that ensure data products are timely, trustworthy, and easy to use.

My core strengths include technical leadership, mentoring, data platform architecture, hands-on delivery, strategic alignment of technical solutions with business objectives, and clear communication of complex concepts to diverse audiences.

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