Data Engineer

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

Location: Buffalo, NY / Remote

Experience: 5+ Years

Position Type: Full-time

Base Salary: $65k

Why HeronAI?

HeronAI lets anyone automate analytics. We’re helping businesses from solo operators to Fortune 100 teams to understand performance, spot inefficiencies, and make smarter decisions in minutes. We believe data analytics shouldn’t be a privilege but a universal right, simple enough for anyone to use to grow their business and transform their industry. With accounting and manufacturing facing massive workforce disruptions (75% of accountants will retire in the next 10 years), we’re stepping in to change how data drives decisions. Backed by MIT, Techstars, and 43North, our platform already empowers mid-sized firms to streamline growth and reporting, cutting analysis time from 12 weeks to under 5 minutes. At HeronAI, you’ll be part of a small team at the forefront of AI-powered decision intelligence, building tools that shift entire industries while seeing your work directly impact customers every day. You’ll also be surrounded by a culture of builders where everyone codes, everyone ships, everyone talks to customers, and has a shared drive to create something magical and world-changing.

Our goal

Our goal not to be just a tool, but to reshape how data drives decisions for over 10 million people in the next 10 years.

What we’re looking for

In one sentence, we’re looking for a data engineer who loves building scalable data infrastructure as much as they love optimizing data pipelines, someone who can turn complex data challenges into robust, automated solutions.

• You have 3-5 years of experience building data infrastructure and pipelines in production environments.
• You have extensive experience with AWS data services (S3, RDS, Redshift, Glue, Lambda, etc.) and understand how to architect scalable data solutions in the cloud.
• You have hands‑on experience with ETL/ELT frameworks, data orchestration tools, and building reliable data pipelines that handle high‑volume workloads.
• You are proficient with Python, SQL, and data processing frameworks, with experience in tools like Dagster, Airflow, or similar orchestration platforms.
• You have experience integrating diverse data sources (APIs, databases, file systems) and transforming raw data into analytics‑ready formats.
• You understand data modeling, warehousing concepts, and best practices for data quality, monitoring, and observability.
• You are obsessed with automation, reliability and documentation so that every pipeline you build is maintainable and scalable.
• You thrive in ambiguity, take action quickly, and get energy from wearing multiple hats in a startup.
• You can clearly communicate technical concepts and collaborate effectively with both technical and non‑technical stakeholders.

What you’ll do

• Build and maintain robust data pipelines that ingest data from spreadsheets, accounting software, CRMs, and other APIs into our data warehouse.
• Design and implement scalable data infrastructure on AWS that can handle growing volumes of customer data.
• Create reusable data transformation templates so every new data source integration becomes faster and more standardized.
• Own data reliability: ensure our pipelines are monitored, alerting, and self‑healing where possible.
• Optimize data pipeline performance and cost efficiency across our AWS infrastructure.
• Collaborate with the product team to understand data requirements and translate them into technical solutions.
• Build and harden backend data integrations that scale with thousands of customers.
• Ensure our data infrastructure is secure, compliant, and enterprise‑ready (SOC2, best practices).
• Implement data quality checks, monitoring, and observability across all data workflows.

Our tech stack

• Backend: Python, Django, Kubernetes
• Data & Integrations: Unified.to, Dagster, Postgres
• Frontend: React, TypeScript, Tailwind
• Cloud & DevOps: AWS (EKS, S3, RDS), Docker, GitHub Actions, Terraform, monitoring & alerting with Sentry
• Tooling & Collaboration: Linear, Slack, Figma