Junior Data Engineer — Pipelines, PySpark & SQL

Madison-Davis, LLC; Woodbridge Township (NJ); On-site; USD 65,000 - 95,000; Full time

Job summary

Madison-Davis, LLC seeks an entry-level Data Engineer to build and maintain data-ingestion processes for enterprise datasets in a modern cloud environment. You will write Python, PySpark, and SQL for data processing and transformations, ensuring data quality and schema enforcement.

As part of the role, you will monitor scheduled workflows, investigate pipeline failures, and collaborate with technical and business teams onboarding data onto the platform.

Qualifications

• Bachelor's degree in CS, Engineering, IS, or related discipline.
• Foundational SQL skills including joins, aggregations, and filtering.
• Hands-on Python programming ability.
• Basic understanding of object-oriented programming.
• Strong understanding of tables, schemas, relational data, and data transformations.
• Exposure to Spark, PySpark, or similar distributed-data technologies.
• Interest in learning Databricks and modern cloud-data platforms.
• Strong problem-solving and attention to detail.
• Ability to communicate clearly and collaborate across teams.

Responsibilities

• Build and maintain data-ingestion processes for enterprise datasets.
• Write Python, PySpark, and SQL for data-processing and transformation tasks.
• Assist with cleansing, validation, reconciliation, and schema enforcement.
• Monitor scheduled workflows and help investigate pipeline failures.
• Collaborate with technical and business teams onboarding data onto the platform.
• Document pipeline logic, transformations, technical decisions, and fixes.
• Participate in code reviews, testing, version control, and deployment processes

Skills

Python programming

SQL

Data transformations

Communication

Team collaboration

Education

Bachelor's degree in CS/Engineering/IS

Tools

PySpark

Spark

Databricks

SQL

Job description

Madison-Davis, LLC seeks an entry-level Data Engineer to build and maintain data-ingestion processes for enterprise datasets in a modern cloud environment. You will write Python, PySpark, and SQL for data processing and transformations, ensuring data quality and schema enforcement.

As part of the role, you will monitor scheduled workflows, investigate pipeline failures, and collaborate with technical and business teams onboarding data onto the platform.