Data Engineer

Monmouth University; Richmond, Northern (VA, KY); Híbrido; USD 90.000 - 120.000; Jornada completa

Descripción de la vacante

Monmouth University in Richmond, VA is seeking an experienced Data Engineer to design, build, and maintain scalable data pipelines using Python, SQL, and modern ETL/ELT techniques in a hybrid work environment. You will work with cloud platforms (AWS, Azure, or GCP) and modern data platforms such as Databricks, Snowflake, Redshift, or BigQuery, plus PySpark for large-scale processing.

Collaborating with analysts, developers, and data scientists, you will ensure data quality, security, and

Formación

• 3-6 years of Data Engineering experience.
• Strong hands-on experience with Python and SQL.
• Experience with ETL/ELT and data pipeline development.
• Experience with PySpark / Apache Spark.
• Experience with Databricks and/or Snowflake.
• Experience with AWS, Azure, or GCP.
• Knowledge of data warehousing and data modeling.
• Experience with Airflow, Azure Data Factory.

Responsabilidades

• Design, develop, and maintain scalable ETL/ELT data pipelines.
• Develop and optimize data processing solutions using Python and SQL.
• Integrate data from multiple structured and unstructured sources.
• Work with cloud platforms such as AWS, Azure, or GCP.
• Work with modern data platforms such as Databricks, Snowflake, Redshift, or BigQuery.
• Monitor, troubleshoot, and optimize data pipelines.
• Ensure data quality, reliability, security, and availability.
• Collaborate with analysts, developers, data scientists, and business teams.

Conocimientos

Python

SQL

ETL/ELT

PySpark

Databricks

Snowflake

AWS/Azure/GCP

Airflow

Data warehousing

Data modeling

Descripción del empleo

Job Type: Contract - W2 Only
Experience: 3-6 Years
Location: Richmond, Virginia - Hybrid

Visa : Opt / H1b transfer also accept

Job Description

We are looking for an experienced Data Engineer to design, develop, and maintain scalable data pipelines and data processing solutions. The ideal candidate should have strong hands-on experience with Python, SQL, ETL/ELT, PySpark, cloud technologies, and modern data platforms.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines.
• Develop and optimize data processing solutions using Python and SQL.
• Integrate data from multiple structured and unstructured sources.
• Work with cloud platforms such as AWS, Azure, or GCP.
• Work with modern data platforms such as Databricks, Snowflake, Redshift, or BigQuery.
• Monitor, troubleshoot, and optimize data pipelines.
• Ensure data quality, reliability, security, and availability.
• Collaborate with analysts, developers, data scientists, and business teams.

Required Skills

• 3-6 years of Data Engineering experience.
• Strong hands-on experience with Python and SQL.
• Strong experience with ETL/ELT and data pipeline development.
• Experience with PySpark / Apache Spark.
• Experience with Databricks and/or Snowflake.
• Experience with AWS, Azure, or GCP.
• Knowledge of data warehousing and data modeling.
• Experience with **Airflow, Azure Data Factory