Junior Data Engineer

Kenect•Pleasant Grove, UT

7d•Onsite

About The Position

Kenect is seeking a Junior Data Engineer to own the movement, quality, and documentation of data across our core business systems. You will build and maintain the pipelines that bring Salesforce, Outreach, Nooks, and other go-to-market systems into BigQuery, then model and document that data so revenue teams can use it with confidence. A meaningful part of this role is discovery and problem-solving: digging into systems to understand where data lives, what it means, and how it maps to real business concepts, then working with the teams who own those systems to translate it for non-technical stakeholders. Documentation matters as much as the pipelines themselves, so that knowledge doesn't live with one person or have to be rediscovered every time someone needs it. This is a high-ownership role on a small team, where what you build goes directly into the hands of the people running the business.

Requirements

1-3 years of experience in data engineering, analytics engineering, or a related role.
Strong SQL skills, including complex joins, window functions, and the ability to write efficient queries that perform well against large datasets
Proficiency in Python for pipeline development and API integrations, along with comfort working in Git-based version control
Experience with a cloud data warehouse, with BigQuery preferred
The ability to make sense of unfamiliar data. You can dig into a new schema, ask the right questions of the engineers and teams who own it, and translate what you learn into clear business terms
Documentation discipline is non-negotiable. If you build it, you document it, clearly enough that someone else can understand, maintain, and build on your work
A figure-it-out mindset. You're comfortable with ambiguity, can scope a problem and move to a practical solution without waiting for every detail to be defined, and you build with an eye toward how it will perform and scale as the business grows

Nice To Haves

A bachelor's degree in a technical field is preferred, but equivalent hands-on experience is equally valuable
Familiarity with dbt and a workflow orchestrator such as Airflow preferred.
Exposure to CRM and go-to-market systems such as Salesforce, Outreach, or similar platforms is preferred.

Responsibilities

Build and maintain ELT pipelines that move data from Salesforce, Outreach, Nooks, and other core business systems into BigQuery, ensuring data is accurate and available when teams need it
Develop and maintain dbt models that transform raw source data into clean, documented, and trustworthy tables
Partner with the engineers who own our product systems to understand how that data is structured, and translate those structures into clear, business-friendly definitions for go-to-market teams
Own data discovery and documentation across systems, identifying where data lives, what individual fields mean, how they relate to one another, and which source should be considered authoritative
Monitor pipeline and orchestration health in Airflow, troubleshoot failures when they occur, identify root causes, and implement lasting fixes rather than temporary workarounds
Partner with go-to-market teams to understand their reporting needs, then translate those requirements into reliable data models that support Power BI and other downstream tools
Support the data infrastructure and evaluation pipelines behind our production AI agent systems running on Modal
Work within Git-based development workflows, using GitHub, CircleCI, and peer code review to ship reliable, well-tested changes
Use AI coding assistants as a standard part of your workflow to learn unfamiliar systems faster and accelerate development, while maintaining strong engineering standards