Junior Data Engineer

Junior Data Engineer at Insight Global

Lensa is promoting this Junior Data Engineer position on behalf of Insight Global, one of the largest logistics and transportation employers in the US. This remote role offers a significant opportunity to contribute to a growing data analytics team, focusing on transforming complex business problems into sustainable data solutions.

Role Overview

As a Junior Data Engineer, you will be integral to understanding business problems and assisting in designing solutions. Your primary focus will be supporting the onboarding of new lines of business into the data analytics team. This involves participating in the full life cycle of data engineering, from gathering requirements from internal customers to building and maintaining data pipelines, testing, and reporting.

Key responsibilities include:

• Assisting in gathering requirements from internal customers.
• Building robust data pipelines from scratch.
• Testing and reporting on data solutions.
• Maintaining existing data engineering solutions.
• Supporting escalation tasks and contributing to system development.
• Helping automate processes and maintaining internal systems.
• Assisting in data modeling, leveraging expertise in company-specific data structures.

Company Culture & Values

Insight Global is committed to creating inclusive environments where employees can thrive. As an equal opportunity employer, they value diversity and ensure fair consideration for employment without regard to various protected characteristics. Reasonable accommodations for disabilities are available during the application process.

Skills and Requirements

Candidates for the Junior Data Engineer position should possess the following qualifications:

• 2-5+ years of data engineering experience.
• Strong experience with Azure Data Factory (ADF), including creating pipelines from scratch and knowledge of connectors and activities.
• Strong SQL knowledge, particularly with SQL scripting for ADF implementation.
• Understanding of the full data engineering life cycle.
• Exceptional attention to detail and ability to provide effective updates.
• Strong communication skills for interacting with internal and external stakeholders.
• Robust critical thinking skills.
• Experience with Python or Spark (basic scripting and reviews in a small Python environment).
• DevOps Experience.
• Data Bricks Experience.
• Background in Logistics is a plus.
• Familiarity with Agile Methodologies.
• Cloud experience, specifically Azure.

Key skills/competency

• Data Engineering
• Azure Data Factory (ADF)
• SQL
• Python
• Spark
• DevOps
• Data Bricks
• Data Modeling
• Cloud Computing (Azure)
• Logistics Domain