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Salary: USD 100,000 - 130,000 / annual
VIA is a mission-critical software company enabling organizations to share and analyze sensitive data securely. The company serves the Department of War, Fortune 50 companies, and critical infrastructure organizations globally, providing decentralized architecture with agentic AI and military-grade security.
As a Data Analytics Engineer, you will be a core contributor to VIA's data product growth. You'll transform complex, ambiguous raw data into clear, trusted narratives that power VIA's solutions and guide customer decisions. Working on a high-velocity Agile team, you'll collaborate 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 paramount.
Key responsibilities include:
**Understanding Data and Domain**: 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 (averages, expected ranges, trends, standard deviations) and make suggestions for data cleaning and analysis.
**Building AI-Powered Data Products**: Deliver data-based products to external customers, including interactive data analysis and investigation platforms, data quality reports, statistical analysis, and visualizations. Build AI into VIA's data products 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 human-in-the-loop checks that keep data products trustworthy.
**Overseeing Data Pipelines**: 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.
**Improving the Platform**: Contribute to the continual improvement of internal tools for data cleaning, modeling, analytics, and data quality assessment by identifying key data-related challenges that are ideal candidates for automation and AI enhancement.
**Requirements:**
- 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: database technologies (SQL, PostgreSQL), data science libraries (NumPy, pandas), data pipelining workflows and tools (Dagster, Airflow, dbt), or cloud providers (AWS, Azure) including SDKs
- Ability to translate complex data findings into clear, compelling narratives
- Strong communication capability to decompose complex operational workflows into clear, repeatable steps that both teammates and AI tools can act on
- Passionate about data integrity with a proven track record of transforming raw inputs into high-quality, trusted datasets
- Self-starter attitude and demonstrated ability to learn new technologies quickly
**Preferred Experience:**
- Generative AI tools (AWS Bedrock, LangChain)
- Testing frameworks (pytest)
