Support the development and delivery of enterprise data products by helping design and validate data pipelines
Document metadata and improve data quality across lakehouse architecture
Assist with ingestion workflows, dashboard testing, lineage mapping, and analytics used by multiple business partners
Prepare training materials, build simple visualizations, and analyze adoption trends

Requirements

Microsoft Azure Fundamentals (AZ-900)
Microsoft Azure Data Fundamentals (DP-900)
Databricks Lakehouse Fundamentals
Foundational knowledge of data engineering concepts, including SQL, data modeling, ETL/ELT pipelines, and cloud platforms
Experience with Python for data manipulation, scripting, or basic automation
Familiarity with cloud data ecosystems such as Azure, Databricks, Snowflake, or AWS
At least 18 years of age
Legally authorized to work in the United States
High School Diploma or GED
Must be actively enrolled in a degree program or graduated within the last year

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLdata modelingETLELTPythondata manipulationdata pipelinesdata qualityanalyticsvisualizations

Soft Skills

documentationtrainingcommunicationcollaborationanalytical thinking

Certifications

Microsoft Azure Fundamentals (AZ-900)Microsoft Azure Data Fundamentals (DP-900)Databricks Lakehouse Fundamentals