Data Analytics Engineer

• Database technologies (e.g., SQL, PostgreSQL)

VIA is making an impact, and so can you.

Headquartered in Boston, Massachusetts, VIA is a mission-critical software company that enables organizations to share and analyze sensitive data at speed without compromising security or control. VIA’s decentralized architecture keeps data sovereign, while its agentic AI helps organizations solve critical challenges, and its military-grade security governs access. Designed for simplicity, rapid deployment, and disconnected environments, VIA makes sensitive data usable wherever the mission happens, even offline.

The Department of War, Fortune 50 companies, and critical infrastructure companies around the globe trust VIA to help them solve their toughest analytics and digital security challenges. Learn more:

As a Data Analytics Engineer at VIA, you'll play a pivotal role in the growth of our solutions. You'll turn raw, complex, and often ambiguous data into the clear, trusted narratives that power VIA's data products and guide our customers' decisions. Operating on a high-velocity Agile team, you'll work cross-functionally with software engineers, data peers, and client delivery professionals to lead data initiatives end to end, in an environment where precision, security, and clarity are non-negotiable.

• Partner with VIA's client delivery team and customers to translate domain knowledge into data infrastructure requirements, validate assumptions, and resolve data-related issues
• Explore customer data to build a clear picture of contents and characteristics (e.g. averages, expected ranges, trends, standard deviations) and make suggestions for data cleaning and analysis

• Deliver data-based products to external customers, including interactive data analysis and investigation platforms, data quality reports, statistical analysis, and visualizations that turn complex findings into clear stories
• Build AI into VIA's data products, for example through automated insights, anomaly detection, AI-assisted data quality checks, and natural-language interfaces over operational data
• Evaluate the quality and reliability of AI/ML outputs against domain expectations, and design the human-in-the-loop checks that keep our data products trustworthy

• Own the design, quality, and reliability of ETL/ELT pipelines, including work built with AI assistance
• Coordinate with internal stakeholders and customers when information is missing or discrepancies are found
• Run quality control on data and data products through both automated tests and targeted manual review, and document the assumptions and decisions made along the way so the work stays traceable

• Contribute to the continual improvement of internal tools for data cleaning, modeling and analytics, and data quality assessment by identifying key data-related challenges that are ideal candidates for automation and AI enhancement

• 3+ years of experience in a data-driven role or equivalent in data-related research projects
• Bachelor’s or Master's degree in science, mathematics, engineering, or a data-driven field
• Competence in Python, R, or equivalent programming language
• Competence in at least two of the following technologies:
  • Database technologies (e.g., SQL, PostgreSQL)
  • Data science libraries (e.g., Num Py, pandas)
  • Data pipelining workflows and tools (e.g., Dagster, Airflow, dbt)
  • Cloud providers (e.g. AWS, Azure), including software development kits used to access data and services on these platforms
• Ability to translate complex data findings into…