Data Engineer, Junior

Role Overview

A Junior Data Engineer supporting the development of cloud-native data products and pipelines to enable enterprise analytics and AI capabilities.

Key Responsibilities

• Write, review, and contribute to code within a collaborative engineering team to build robust technical solutions.
• Design and deploy high-performance, cloud-based data components for enterprise use.
• Build and maintain reusable data platform features, ingestion frameworks, and data products (using tools like dbt, Azure Logic Apps, and Snowflake).
• Support reliable data pipeline operations, including monitoring, testing, and recovery.
• Maintain synchronization between source systems and cloud platforms.
• Develop scalable data transformation pipelines to facilitate analytics and AI-driven insights.
• Implement data engineering best practices, such as CI/CD, testing, and code reviews.
• Contribute ideas to the team's data engineering roadmap as skills develop.

Requirements & Tech Stack

• Proficiency in Python and SQL.
• Experience with Azure and/or AWS cloud platforms.
• Knowledge of ELT processes, data modeling, and transformation frameworks like dbt.
• Familiarity with data warehousing platforms such as Snowflake or Databricks.
• Exposure to data processing technologies like Apache Spark or streaming systems is advantageous.
• Understanding of CI/CD pipelines and Infrastructure as Code tools like Terraform or GitHub Actions.
• Experience designing or supporting large-scale data pipelines, with a strong desire to grow expertise in data architecture, observability, and best practices.
• Effective communication skills for working with technical teams and business stakeholders.
• Educational background in Computer Science or related experience.

Preferred Qualifications

• Interest or experience with GenAI, LLMs, vector search, or agentic workflows.
• Background in food service, hospitality, retail, or consumer industries.