Data Engineer

As a Data Engineer, you will focus on developing data pipelines for multi-functional teams, ultimately empowering the organization to make more data-driven decisions. You will be responsible for building data pipelines from source to consumption layer, following the medallion architecture (Bronze, Silver, Gold). Leveraging a technology stack that includes Snowflake, dbt, Python, and SQL, you will assemble large, sophisticated data sets that meet functional and non-functional business requirements. Working with various stakeholders, you will gather requirements and deliver compliant, efficient, sustainable, and well-documented solutions.

This position is based out of the Piscataway, NJ location. Work visa sponsorship is not available for this position.

What you'll do

• Design, build, and maintain production data pipelines from ingestion to consumption using Snowflake, dbt, Python, and SQL following Medallion Architecture standards.
• Assemble large-scale, complex datasets aligned with enterprise standards while optimizing infrastructure for performance and cost.
• Drive continuous pipeline improvement by automating manual workflows, tuning query execution, and evaluating emerging data technology.
• Partner with business and IT stakeholders to translate functional requirements into scalable data delivery solutions and resolve technical pipeline blockers.
• Enforce code quality and enterprise compliance through peer GitHub code reviews, technical documentation, and pipeline design standards.

Required Qualifications

• Bachelor’s Degree in Computer Science, Information Technology, Engineering, or a related field.

• 2+ years of professional experience as a Data Engineer or related role.

• Proven experience in Python, SQL, and cloud infrastructure (AWS/GCP), with hands-on expertise building scalable data pipelines, managing databases, and utilizing Git, containerization (Docker/Kubernetes), Terraform, Airflow, and Snowflake/dbt.

Preferred Qualifications

• Previous experience in a Data Engineering role working closely with other programmers (Software Engineers, Data Scientists, etc.).
• Experience in network, server, and application-status monitoring.
• Familiarity with software-automation production systems (GitHub Actions, Selenium, etc.).
• Familiarity with code deployment tools.
• Familiarity with preparing datasets for AI/ML models, vector embeddings, or feature engineering.