Senior Data Engineer

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 DATA TEAM

The Data Science team at GenLogs transforms raw observational data from the Trident sensor network into high-value intelligence used by law-enforcement agencies, regulators, ports, and private-sector freight operators. We build models, analytics, and measurement frameworks that enable vehicle detection, entity resolution, behavioral insights, fraud and theft indicators, compliance signals, and network-wide operational performance metrics. Our work sits at the center of the freight intelligence platform, shaping how billions of roadside observations become actionable information. We partner closely with Engineering and Product to deploy algorithms at scale and with Go-to-Market teams to define customer-facing analyses that drive real operational outcomes. The team blends statistical rigor, ML capability, and domain expertise to create a new standard for freight intelligence in the United States.

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.

• 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.
• Lead data engineering best practices and influence architectural decisions.
• Drive projects independently, from definition to delivery.
• Collaborate with engineering, analytics, and ML teams to support shared goals.

• 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.

• 5+ 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.

• 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.

You will love this role if you are:

• Relentlessly curious — you ask “why?” repeatedly until you reach the root
• Technically fearless — not afraid to dive into large datasets, new ML techniques, or unfamiliar codebases
• Impact-driven — you want your models to power real, high-stakes decisions in a massive industry
• Comfortable with ambiguity — our data is large, messy, and evolving, and that excites you
• Collaborative — you enjoy working with engineers, data teams, and product stakeholders to deliver real customer value

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.

• Employer-covered comprehensive medical, dental, and vision plans
• Employer contribution towards premiums of optional higher-end plans

• Unlimited PTO
• Sick leave
• Company holidays (GenLogs observes all US Government holidays)
• Flexible leave for caregiving and medical needs

• Paid parental leave

• Budget availability for approved professional development courses, certifications, and training

• 100% travel reimbursement for all approved company travel and spending

• 401(k) plan (US based employees)

A recruiter can provide more detail about the specific compensation and benefits associated with this role.