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Salary: USD 140,000 - 160,000 / 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 with decentralized architecture, agentic AI, and military-grade security.
As a Senior Data Analytics Engineer, you will be a key technical contributor responsible for transforming complex, raw data into clear, trusted narratives that power VIA's data products and guide customer decisions. You'll operate on a high-velocity Agile team, working cross-functionally with software engineers, data peers, and client delivery professionals to lead data initiatives end to end.
Key responsibilities include:
**Understanding Data & 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, and make suggestions for data cleaning and analysis.
**Building AI-Powered Data Products**: Deliver data-based products to external customers, including interactive data analysis 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, documenting assumptions and decisions to maintain traceability.
**Platform Improvement**: Contribute to continual improvement of internal tools for data cleaning, modeling, analytics, and data quality assessment by identifying key data-related challenges ideal for automation and AI enhancement.
You bring 5+ years of experience in data-driven roles, including owning data initiatives end to end. You hold a Bachelor's or Master's degree in science, mathematics, engineering, or a related field. You're proficient in Python, R, or equivalent programming languages, and competent in at least three of: SQL/database technologies, data science libraries (NumPy, pandas), data pipelining tools (Dagster, Airflow, dbt), or cloud providers (AWS, Azure). You excel at translating complex data findings into clear narratives and decomposing complex workflows into repeatable steps. You're passionate about data integrity and have a proven track record of transforming raw inputs into high-quality, trusted datasets. Plus experience with generative AI tools and testing frameworks is valued.
