Ben Gislason

Data engineer with experience building data pipelines, automation scripts, and quality assurance processes for large, multi-source scientific and operational datasets. Proficient in SQL and Python/R for data pipeline development, automation, and integration across cloud and on-premises systems, with hands-on experience in data standards, governance, and documentation practices (ISO 9001, ISO 17025).

Background includes modernizing legacy data and instrumentation systems, implementing version control and QA/QC processes, and developing metadata and compliance documentation to meet regulatory standards (IEEE 1547). Experienced working independently and within cross-functional teams to centralize, standardize, and migrate disparate datasets onto sustainable, scalable platforms, with strong organizational and communication skills suited to dynamic, multi-priority environments.

Associate - The Cadmus Group

(2025-06)

• Build and maintain automated Python-based data pipelines on Azure to centralize, standardize, and process large, multi-faceted scientific and utility datasets into a unified data architecture.
• Design and implement automated data quality assurance processes (ISO 9001-aligned) in Databricks, including validation, documentation, and version-controlled workflows to ensure data integrity across the pipeline.
• Develop and maintain a standardized data architecture (Medallion Bronze/Silver/Gold in Delta Lake) incorporating machine learning models and spatial/GIS data workflows (ArcGIS), aligning disparate source datasets to a consistent structure to support downstream sharing and analysis.
• Author and maintain automation scripts for data transfer, transformation, and distribution between cloud platforms (YAML/JSON, Azure Databricks).
• Develop metadata and documentation standards for model and pipeline outputs, supporting reproducibility and compliance with data quality requirements.
• Collaborate cross-functionally with data scientists and analysts to standardize tooling and documentation practices across the team.

Senior Analyst - The Cadmus Group

(2022-04 - 2025-06)

• Developed automated data pipelines (Python, R, SQL) to ingest, clean, and integrate large, multi-source datasets supporting technology and energy modeling studies.
• Designed and maintained cloud-based data storage and processing systems (Databricks, Delta Lake), implementing data quality and documentation procedures for long-term sustainability.
• Led data pipeline and software development initiatives, managing version control (Git/GitLab) and working both independently and as part of a cross-functional team to meet project timelines.
• Built Power BI dashboards and visualization tools, translating complex datasets into clear, accessible outputs for technical and non-technical stakeholders.

Data / Lead Data Systems Engineer - Clemson University

(2016-04 - 2022-04)

• Designed and implemented data pipelines and database systems (PostgreSQL/MySQL) for large-scale scientific testing labs, centralizing and standardizing data from multi-node distributed sensor systems into a unified structure.
• Modernized legacy data acquisition and instrumentation systems, migrating to scalable, automated real-time monitoring platforms with improved reliability and accessibility.
• Implemented data quality assurance processes including version control, automated validation, backup procedures, and documentation to ensure data integrity across the full data lifecycle.
• Built custom data analytics and visualization applications (Python, MATLAB, Power BI) incorporating statistical models, automating data analysis and distribution workflows.
• Established GitHub-based version control practices and developed ISO 17025-certified documentation and metadata standards, ensuring compliance with quality requirements and supporting audit-ready data governance.

Research Engineer - Clemson University

(2013-05 - 2016-04)

• Authored and executed scripts of varying complexity (MATLAB, LabVIEW) for automated data production, processing, and compliance reporting (IEEE 1547 DER) in a scientific instrumentation environment.
• Designed and implemented real-time data acquisition systems for a multi-megawatt testing facility, establishing data collection protocols and documentation standards from initial system commissioning.
• Co-authored peer-reviewed research papers involving data integration and instrumentation methodologies, demonstrating strong written and verbal communication skills across technical audiences.

Bachelor of Applied Science - Electrical & Computer Engineering - The Citadel (2013-04)