AI-Powered Data Analytics Engineer — Build Trusted Insights

Solve With Via; Somerville, Northern (MA, KY); Hybrid; USD 100,000 - 130,000; Full time

Benefits offered by this job

Salary range

401K match

Health benefits

Parental leave

Flexible vacation

Remote work

Mentorship programs

Wellness program

Transit benefits

Job summary

VIA, a digital infrastructure company, is seeking a Data Analytics Engineer to turn raw data into trusted narratives that power VIA's data products for clients. You’ll work on high-velocity Agile teams across client delivery, engineering, and data peers to drive data initiatives end-to-end.

You'll build AI-powered data products, ensure data quality, and own ETL/ELT pipelines with automated tests, while improving internal tooling for data cleaning, modeling, and analytics.

Qualifications

• 3+ years in a data-driven role or equivalent in data-related projects
• Bachelor’s or Master’s degree in science, mathematics, engineering, or data-driven field
• Competence in Python, R, or equivalent programming language

Responsibilities

• Understand the data and the domain: translate domain knowledge into data infrastructure requirements and validate assumptions
• Build AI-powered data products: interactive data analysis, quality reports, and visualizations; AI-enabled data quality checks
• Oversee data pipelines: design, quality, and reliability of ETL/ELT pipelines; coordinate with stakeholders
• Improve the platform: enhance internal tools for data cleaning, modeling, analytics, and data quality automation

Skills

Python

R

NumPy

Pandas

Dagster

Airflow

dbt

AWS

Azure

Data storytelling

Communication

Self-motivated

Education

Bachelor/Master in STEM

Tools

Dagster

Airflow

dbt

Job description

VIA, a digital infrastructure company, is seeking a Data Analytics Engineer to turn raw data into trusted narratives that power VIA's data products for clients. You’ll work on high-velocity Agile teams across client delivery, engineering, and data peers to drive data initiatives end-to-end.

You'll build AI-powered data products, ensure data quality, and own ETL/ELT pipelines with automated tests, while improving internal tooling for data cleaning, modeling, and analytics.