Data Engineer

Role Overview

• 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.

Requirements

• 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
• 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.

Tech Stack

• Airflow
• AWS
• ETL
• Python
• SQL

Benefits

• Healthcare (US based only)
• 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.