Data Engineer
New York, remote, mid, full time, 2–5 years
posted 29 Sept 2026
- Airflow
- PostgreSQL
- Next.js
- GitHub Actions
- Cloud Run
- Elasticsearch
- Neo4j
- Docker
- Terraform
- Snowflake
- Trino
- AWS
- Python
- Azure
- Model Context Protocol
- Google Cloud Platform
- APIs
- Presto
- GCS
- Starburst
- Apache Beam
- FastAPI
- MongoDB
- Spark
- Databricks
About the role
Data Engineer
Job Type: Full time Location: Remote
We are searching for an ambitious go getter who welcomes the challenge of meeting the needs of a hyper growth startup. As a Data Engineer, you will contribute to the company's data infrastructure, playing a key role in developing and maintaining the systems that power its AI platform. Your work will directly influence product features, client outcomes, and strategic business decisions.
You will collaborate with Forward Deployed Engineers, Data Scientists, Backend Engineers, Client IT, and business stakeholders to build and support scalable pipelines that serve billions of rows of structured and unstructured data weekly, enabling high impact insights across multiple industries.
What you would do
Technical Development
* Implement and support scalable, high performance data infrastructure to handle complex data processing and integration across platforms
* Extract and ingest data from a wide variety of structured and unstructured web sources
* Develop developer facing tools, abstractions, and frameworks that empower engineering teams to easily build and manage data pipelines
* Leverage modern cloud platforms (e.g., Snowflake, Databricks) to execute ETL jobs, share data securely, and enforce granular access controls
* Work with AI driven autonomous agents to streamline data operations and enable advanced data exploration on client datasets
* Engineer and manage resilient ETL/ELT pipelines using tools like Airflow, Snowpark, Databricks, Cloud Run, and Apache Beam
* Define, deploy, and maintain data infrastructure using Infrastructure as Code (IaC) principles
Collaboration
* Partner with Forward Deployed Engineers and Data Scientists to translate business and machine learning requirements into production ready data workflows
* Ensure consistent, timely delivery of clean, high quality data to drive model development and core product features
Monitoring and Reliability
* Create and manage real time monitoring systems for data ingestion and transformation pipelines
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