Data Engineer

Southern Arkansas University; Warner Robins (GA); Remote; USD 22,750 - 45,500; Part time

Benefits offered by this job

Flexible hours

Weekly bonus of $500–$1000 USD

Work from anywhere

Job summary

A leading AI lab is seeking a Data Engineer to design and maintain scalable ETL/ELT pipelines ensuring high-quality data for analytics and machine learning. Candidates should have a background in computer science, proficiency in Python and SQL, and experience with data engineering tools. This part-time role (20-30 hours/week) offers flexible hours and a bonus structure based on performance.

Qualifications

• Proficiency in Python, pandas, and SQL.
• Hands-on experience with databases like PostgreSQL or SQLite.
• Understanding of distributed data processing with Spark or Duck DB.

Responsibilities

• Build and maintain ETL/ELT pipelines focusing on scalability and resilience.
• Validate and enrich datasets to ensure they're analytics- and ML-ready.
• Manage schemas, versioning, and data contracts to maintain consistency.

Skills

Python

SQL

Data pipeline development

Distributed data processing

Schema design

Version control with Git

Data quality assurance

Education

Background in computer science, data engineering, or information systems

Tools

PostgreSQL

SQLite

Spark

Airflow

Job description

Hiring a Data Engineer on behalf of a leading AI lab. In this role, you’ll design resilient ETL/ELT pipelines and data contracts to ensure datasets are analytics- and ML-ready. You’ll validate, enrich, and serve data with strong schema and versioning discipline, building the backbone that powers AI research and production systems. This position is ideal for candidates who love working with data pipelines, distributed processing, and ensuring data quality at scale.

Qualifications

• Background in computer science, data engineering, or information systems
• Proficiency in Python, pandas, and SQL
• Hands‑on experience with databases like PostgreSQL or SQLite
• Understanding of distributed data processing with Spark or Duck DB
• Experience orchestrating workflows with Airflow or similar tools
• Comfortable with common data formats such as JSON, CSV, and Parquet
• Passion for schema design, data contracts, and version control with Git
• Drive to build pipelines that enable reliable analytics and ML workflows

Primary Goal of This Role

To design, validate, and maintain scalable ETL/ELT pipelines and data contracts that produce clean, reliable, and reproducible datasets for analytics and machine learning systems.

What You’ll Do

• Build and maintain ETL/ELT pipelines with a focus on scalability and resilience
• Validate and enrich datasets to ensure they’re analytics- and ML-ready
• Manage schemas, versioning, and data contracts to maintain consistency
• Work with PostgreSQL/SQLite, Spark/Duck DB, and Airflow to manage workflows
• Optimize pipelines for performance and reliability using Python and pandas
• Collaborate with researchers and engineers to ensure data pipelines align with product and research needs

Why This Role Is Exciting

• You’ll create the data backbone that powers cutting‑edge AI research and applications
• You’ll work with modern data infrastructure and orchestration tools
• You’ll ensure reproducibility and reliability in high‑stakes data workflows
• You’ll operate at the intersection of data engineering, AI, and scalable systems

Pay & Work Structure

• You’ll be classified as an hourly contractor
• Paid weekly via Stripe Connect, based on hours logged
• Part‑time (20–30 hour/week) with flexible hours—work from anywhere, on your schedule
• Weekly bonus of $500–$1000 USD per 5 tasks