Junior Data Engineer

Apprenticely•Fayetteville, NC

12d•$20 - $30

About The Position

The Junior Data Engineer at the Walton Arts Center and Walmart AMP is a critical role responsible for building and maintaining data systems, data warehouses, and data pipelines to enable data-driven decision-making. This role collaborates with the Senior Director of Technology Services and other teams to strategize and implement roadmaps for data management, ensuring data integrity, security, and accessibility across platforms.

Requirements

Strong SQL skills, including SELECT/INSERT/UPDATE/DELETE, JOINs, GROUP BY, window functions, and query optimization.
Experience with Snowflake: data loading, COPY commands, warehouse usage, JSON parsing, tables, and views.
Familiarity with SQL Server, PostgreSQL/MySQL, and general relational database concepts.
Basic understanding of the Azure ecosystem (Blob Storage, Functions, Monitor) and AWS services (S3, Lambda).
Python skills for scripting, API calls, data manipulation with pandas/numpy, file processing, and automation tasks.
Power BI fundamentals: data modeling, relationships, basic DAX, and report/dashboard building.
Strong Excel skills: advanced formulas, pivot tables, and data analysis.
Understanding of ETL/ELT concepts, pipeline design, and data modeling best practices.
Ability to work with multiple file formats including CSV, JSON, XML, and Parquet.
Experience with version control (Git), branching strategies, and collaboration workflows.
Basic DevOps understanding: deployments, environments, monitoring, and resource troubleshooting.
Awareness of cost optimization principles for cloud platforms and data operations.
Strong analytical and problem-solving skills, with the ability to debug and resolve data issues quickly.
Ability to communicate clearly with both technical and non-technical stakeholders.
Experience gathering requirements from business users and translating them into reporting or data solutions.
Demonstrated ability to create clean, concise technical documentation.
Understanding of data governance fundamentals including privacy, security, and compliance.
Ability to present insights in a clear, structured, and accessible way (“data storytelling”).
Ability to work independently while also collaborating closely with the Director of Technology Services, Data Engineer, and Technology Services team.
Strong attention to detail, consistency, and accuracy.
Must be able to lift and carry up to 50 lbs.
Ability to sit or stand for extended periods.
Must be able to work under pressure and meet deadlines.
Ability to work independently and within a team.
Occasional evening and weekend work required for events.

Responsibilities

Build and maintain reliable ETL/ELT pipelines that move data from core systems (ticketing, CRM, F&B, digital platforms, finance systems, etc.) into Snowflake.
Write clean SQL queries, views, and transformations across SQL Server, Snowflake, and PostgreSQL/MySQL in support of analytics, dashboards, and operational needs.
Perform routine data quality checks, validation steps, and error handling to ensure accuracy and trust in our data sources.
Assist in integrating cloud storage systems (Azure Blob, AWS S3) with Snowflake using COPY commands, file stages, and automated workflows.
Develop and schedule batch jobs and automated processes to keep data refreshed across systems.
Support Power BI dashboard development by preparing optimized datasets, modeling relationships, monitoring refresh schedules, and resolving performance issues.0
Partner with business units to gather report requirements, translate them into technical specifications, and deliver clear and actionable insights.
Monitor daily pipelines, system performance, and data model health, escalating issues before they impact the business.
Troubleshoot and debug data failures, broken feeds, or mismatched numbers between source systems and Snowflake.
Document data flows, pipeline logic, table definitions, and reporting standards to maintain clarity and consistency across the Technology Services division.
Participate in data governance efforts, including privacy, security, and compliance alignment across platforms.
Support AI and automation initiatives by preparing datasets for analysis, assisting with feature engineering, and validating model outputs when needed.