Data Engineer

GenLogs Corporation Open · verified Oct 24, 2026

Remote United States Full-time Mid-level Data Engineering

At a glance

Mid-level Data Engineering role at GenLogs Corporation. Remote, United States · full-time · no salary stated · we estimate $112,500–$160,000 across the United States.

Estimated pay

GenLogs Corporation has not published a salary for this role. The figure below is our estimate, not theirs.

$112,500 – $160,000

What the middle half of mid-level data engineering roles in the United States paid, among postings that did state a salary.

Worked out from 386 postings that stated pay, median $134,547. Last updated Oct 24, 2026.

RoleData Engineering

SeniorityMid-level

LocationUnited States

WorkplaceRemote

EmploymentFull-time

PostedDec 10, 2025 · 10mo ago

Role brief

dataroles summary, based on the employer's posting.

What you'll do

Build and maintain Python and SQL pipelines that move data through ETL and ELT workflows
Set up ingestion with AWS Firehose and S3, then shape the data in dbt models and tests
Improve Airflow workflows and Snowflake queries to support dependable runs and efficient warehouse use
Protect data quality and pipeline service commitments with validation checks and monitoring
Prepare feature data for machine learning, then help deploy, monitor and retrain models

What you bring

At least three years in data engineering or software engineering
Strong working ability in both Python and SQL
Practical experience with Snowflake, AWS Firehose or S3, Airflow and dbt

Who this fits

This role suits an independent engineer who can turn unclear data problems into practical steps and values careful problem-solving. It is a full-time remote position for someone based in the United States.

From the employer

GenLogs is a transportation-technology company building the next generation of truck intelligence. Through a nationwide network of sensors and proprietary data, we deliver real-time, high-fidelity insights into freight movement for commercial supply-chain customers and public-sector agencies. Our mission is to strengthen America’s logistics backbone, combat freight fraud and cargo theft, and provide near-instantaneous visibility into commercial motor vehicle activity across major freight corridors. By operating at the intersection of edge sensing, computer vision, AI-driven analytics, and large-scale field deployment, GenLogs is transforming how transportation data is captured, secured, and commercialized.

ABOUT THE JOB

You’re a problem solver at heart. You thrive at the intersection of engineering, computer science, and data, you’re motivated by questions that don’t have obvious answers, and you love to architect and build reliable systems that enable whole organizations to build world class analytics. You bring a background in engineering, computer science, physics, applied math, or another hard science discipline, and you enjoy applying that technical foundation to real-world data challenges.

You are energized by ambiguity, obsessed with understanding how complex systems behave, and capable of breaking down big problems into tractable iterations. You ask great questions, validate assumptions with data, and are relentless in your pursuit of signal over noise.

WHAT YOU’LL DO

Build and maintain ETL/ELT pipelines using Python and SQL.
Develop ingestion workflows with AWS Firehose, S3, and related services.
Create and optimize dbt models, tests, and incremental logic.
Tune Snowflake queries and warehouse usage for cost and performance.
Operate and improve Airflow DAGs for reliable execution and monitoring.
Maintain high data quality, data integrity, and pipeline SLA commitments.

Bring clarity to ambiguous requirements and propose practical solutions.

Build feature pipelines to support ML workflows.
Support model deployment, monitoring, and automated retraining.
Add data validation and quality checks across ML and analytics pipelines.

REQUIRED QUALIFICATIONS

3+ years of experience in data engineering or software engineering.
Strong Python and SQL skills.
Hands-on experience with Snowflake, AWS Firehose/S3, Airflow, and dbt.
Ability to work independently and execute in a dynamic environment.
Strong problem-solving skills and attention to detail.

PREFERRED QUALIFICATIONS

Experience with geospatial data (e.g., spatial joins, geometry processing, or geospatial libraries).
Experience with ML or MLOps pipelines.
Knowledge of Snowflake streams, tasks, and performance tuning.
Experience with large-scale or semi-structured datasets.

WHO WILL SUCCEED HERE

US SALARY RANGE

GenLogs establishes compensation based on role, level, experience, and location. Salary bands are benchmarked against high-growth technology companies and adjusted for market conditions. Equity grants are included in most full-time offers to ensure every team member participates in the company’s long-term value creation. A recruiter will provide a precise range during the hiring process.