Data Engineer: Real-Time Analytics & ML Pipelines

GenLogs Corporation; United States; Remote; USD 110,000 - 170,000; Full time

Benefits offered by this job

Healthcare (US based)

Unlimited PTO

Sick leave

Company holidays

Flexible leave for caregiving

Paid parental leave

Professional development budget

Travel reimbursement

401(k) plan

Job summary

GenLogs is a transportation-technology company building the next generation of truck intelligence. You will architect and implement reliable data pipelines, mastering Python, SQL, Snowflake, Airflow and dbt to enable organization-wide analytics and ML workflows.

You will tackle ambiguous problems, validate assumptions with data, and ensure data quality and timely delivery in a dynamic environment. This role offers substantial impact in optimizing freight insights and operations.

Qualifications

• 3+ years of data engineering or software engineering.
• Strong Python and SQL skills.
• Hands-on experience with Snowflake, AWS Firehose/S3, Airflow, and dbt.

Responsibilities

• 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 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.

Skills

Python

SQL

Data Engineering

Tools

Snowflake

AWS Firehose/S3

Airflow

dbt

Job description

GenLogs is a transportation-technology company building the next generation of truck intelligence. You will architect and implement reliable data pipelines, mastering Python, SQL, Snowflake, Airflow and dbt to enable organization-wide analytics and ML workflows.

You will tackle ambiguous problems, validate assumptions with data, and ensure data quality and timely delivery in a dynamic environment. This role offers substantial impact in optimizing freight insights and operations.