Data Engineer

Kendall Howard•Chisago City, MN

30d•$80,000 - $120,000•Onsite

About The Position

The Data Engineer builds and maintains the data layer of Kendall Howard's industrial telemetry platform. This role designs the database, develops data pipelines that transform raw machine telemetry into actionable insights, and creates dashboards used by service technicians for equipment monitoring and predictive maintenance. Working closely with IoT Systems Engineering and Service teams, you'll help shape a new platform as it scales across a growing fleet.

Requirements

Bachelor's degree in Computer Science, Data Engineering, Software Engineering, or related field (or equivalent experience).
2+ years of experience in data engineering, database engineering, or analytics engineering.
Strong SQL skills and experience with relational databases (PostgreSQL preferred).
Experience building ETL/ELT pipelines using Python or a similar language.
Experience creating dashboards using Grafana, Power BI, or similar tools.
Ability to work on-site in Chisago City, MN.
Authorized to work in the U.S. without sponsorship.

Nice To Haves

Time-series databases (TimescaleDB, InfluxDB, or similar).
IoT, telemetry, or machine-generated data.
Database optimization, partitioning, and retention strategies.
Workflow orchestration and production data pipelines.
Operational dashboards, alerting, anomaly detection, and trend analysis.
MQTT, edge systems, battery management, motor controls, or industrial equipment telemetry.
Machine learning or predictive maintenance concepts.
Building new products or platforms in an early-stage environment.

Responsibilities

Design and maintain database schemas, asset models, and retention strategies.
Implement scalable storage solutions for time-series and relational data.
Optimize database performance and manage schema migrations.
Develop ETL/ELT pipelines to ingest, validate, transform, and normalize machine telemetry.
Build parsing logic for sensor, diagnostic, and event-log data.
Collaborate with IoT engineers on data contracts and payload structure.
Build dashboards and visualizations for equipment monitoring.
Develop historical and real-time trending, alerting, and predictive maintenance reporting.
Improve dashboards based on feedback from engineering and service teams.
Troubleshoot data quality and reporting issues.
Maintain documentation, data dictionaries, and version control for database and transformation code.