Associate Enterprise Data Engineer

Responsibilities

• Assist in developing, testing, and maintaining data pipelines and integration workflows for batch processing, under senior engineer supervision.
• Support ETL/ELT tasks by writing and debugging basic data transformation scripts for structured data sources.
• Assist with configuring and running Microsoft Fabric components (Data Factory pipelines, Lakehouse tables, basic notebooks) as directed by senior engineers.
• Write, test, and troubleshoot basic-to-intermediate SQL queries, views, and simple stored procedures under review.
• Support the maintenance of data models, data marts, and analytical datasets by performing assigned data entry, validation, and update tasks.
• Perform data quality checks, including basic validation and reconciliation tasks, and escalate anomalies to senior team members.
• Assist with testing activities during platform migrations and cloud environment updates under supervision.
• Use version control (Git) to commit and track code changes, and follow established coding standards and peer review processes.
• Support the application of basic data security practices and access control configurations as instructed by senior staff.
• Participate in daily stand-ups, sprint planning, and team meetings, and communicate progress and blockers clearly.
• Document completed work, update runbooks, and prepare basic technical notes to support knowledge transfer.

Qualifications

• Bachelors degree in Computer Science, Information Systems, Software Engineering, Data Science, Information Technology, or a related technical discipline (or equivalent practical experience).
• Relevant certifications or coursework in cloud data platforms (e.g., Microsoft Fabric, Azure Fundamentals, SQL, Python) completed through bootcamps, or university programs.
• 1 to 2 years of experience in data engineering, data analytics, or a related technical field, which may include internships, co-ops, academic capstone projects, or entry-level professional roles.
• Exposure to SQL and at least one programming language (e.g., Python) through coursework, internships, personal projects, or an entry-level role.
• Basic exposure to building or maintaining simple data pipelines or ETL scripts, whether in a classroom, internship, or self-directed project setting.
• Some exposure to a cloud platform (Microsoft Azure required) through coursework, certification, personal projects, or an internship.
• Experience working in a team-based or Agile/Scrum project setting, including group academic projects, internships, or hackathons.

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