Cloud Data Engineer - ETL/ELT & Snowflake/dbt

Princeton University; Princeton (NJ); On-site; USD 120,000 - 135,000; Full time

Job summary

Princeton University is seeking a Data Engineer to own and evolve our data integration practice. You will ingest data from enterprise sources into our data warehouse and lead migration to a cloud-native platform.

Key focus areas include ETL/ELT pipeline design, data quality, security, and CI/CD for data deployments. Strong SQL, Python, and Linux tooling are essential, with a bachelor’s in CS required.

Qualifications

• 5+ years of proven experience with enterprise ETL/ELT tooling.
• Advanced SQL skills across Oracle, SQL Server, PostgreSQL.
• Strong Python for data transformation and automation.
• Shell scripting for batch jobs on Linux/Unix servers.
• Hands-on with at least one cloud data platform (Fabric/Snowflake/Databricks).
• Experience with dbt for transformation layers.
• Documentation of data flows, pipelines, and logic.

Responsibilities

• Design, build, and maintain ETL/ELT pipelines to load data into the data warehouse.
• Lead migration of on-prem pipelines to a cloud-native platform (Fabric/Snowflake/Databricks).
• Implement data quality checks, lineage, and pipeline observability.
• Ensure data security, encryption, and IAM-aligned access controls.
• Collaborate with analysts and BI developers to translate data requirements.
• Develop pipeline documentation, data dictionaries, and SLAs; participate in on-call rotation.
• Contribute to CI/CD practices for data integration deployments.

Skills

Linux / Shell scripting

Python programming

SQL

Networking basics

Cloud infrastructure fundamentals

IAM

REST APIs

Data flow documentation

Education

Bachelor’s degree in computer science

Tools

Snowflake

dbt

Fivetran

Databricks

Microsoft Fabric

IBM DataStage

Job description

Princeton University is seeking a Data Engineer to own and evolve our data integration practice. You will ingest data from enterprise sources into our data warehouse and lead migration to a cloud-native platform.

Key focus areas include ETL/ELT pipeline design, data quality, security, and CI/CD for data deployments. Strong SQL, Python, and Linux tooling are essential, with a bachelor’s in CS required.