Data Engineer - Remote & AWS Pipelines

HeronAI; Buffalo (NY); Hybrid; USD 59,000 - 72,000; Full time

Job summary

HeronAI is seeking a data engineer in Buffalo/remote to build scalable data pipelines and infrastructure. You will ingest data from spreadsheets, accounting software, CRMs and APIs into our data warehouse and design AWS-based solutions for growing data volumes.

The role requires 3–5 years of production data engineering experience, strong Python/SQL skills, and hands-on practice with Dagster or Airflow. You’ll collaborate with product teams and ensure secure, reliable, and observable data systems.

Qualifications

• 3–5 years of experience building data infrastructure and pipelines in production.
• Extensive experience with AWS data services and scalable cloud data solutions.
• Hands-on ETL/ELT, data orchestration, and reliable pipelines for high-volume workloads.
• Proficiency in Python, SQL and data processing frameworks; experience with Dagster or Airflow.
• Experience integrating APIs, databases and file systems into analytics-ready formats.

Responsibilities

• Build and maintain data pipelines ingesting data from spreadsheets, accounting software, CRMs and APIs into a data warehouse.
• Design scalable data infrastructure on AWS to handle growing customer data.
• Create reusable data transformation templates for new data source integrations.
• Own data reliability: monitoring, alerting, and self-healing pipelines.
• Optimize pipeline performance and cost across AWS infrastructure.
• Collaborate with product to translate data requirements into solutions.
• Build and harden backend data integrations for thousands of customers.
• Ensure data infrastructure is secure, SOC2-aligned and enterprise-ready.
• Implement data quality checks, monitoring and observability.

Skills

Python

SQL

Data modeling

Cloud architecture

Tools

Dagster

Airflow

AWS

Postgres

Kubernetes

Job description

HeronAI is seeking a data engineer in Buffalo/remote to build scalable data pipelines and infrastructure. You will ingest data from spreadsheets, accounting software, CRMs and APIs into our data warehouse and design AWS-based solutions for growing data volumes.

The role requires 3–5 years of production data engineering experience, strong Python/SQL skills, and hands-on practice with Dagster or Airflow. You’ll collaborate with product teams and ensure secure, reliable, and observable data systems.