Remote Data Engineer - AI/ML Data Pipelines

Pantheon Data; Reston (VA); Remote; USD 110,000 - 190,000; Full time

Benefits offered by this job

SmartBenefits

Tuition assistance

SmarTrip pre-tax

Job summary

Pantheon Data is seeking a hands-on Data Engineer to design, build, and operate data foundations for analytics, AI/ML, and intelligent document processing. You will own data pipelines and stores, collaborating with ML engineers to ensure reliable, scalable data delivery across structured, semi-structured, and unstructured data in various stores.

Strong Python/SQL and AWS experience are highly valued. The role emphasizes data quality, lineage, orchestration, and operational monitoring, with

Qualifications

• Bachelor's degree in CS/Engineering or related field.
• 5+ years of professional data engineering or related experience.
• Strong Python programming and SQL skills with production-ready code.

Responsibilities

• Design, build, and maintain reliable data pipelines across data types.
• Develop Python-based processing workflows for ingestion, normalization, and transformation.
• Work with SQL and relational stores for transactional and analytical use cases.
• Model relationships using graph databases and query languages like ArangoDB/AQL.
• Build vector data pipelines and embeddings for AI/ML support.
• Collaborate with ML engineers, cloud engineers, and product stakeholders.

Skills

Python

SQL

Data modeling

ETL/ELT

Airflow

Git

ArangoDB/AQL

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

ArangoDB/AQL

Job description

Pantheon Data is seeking a hands-on Data Engineer to design, build, and operate data foundations for analytics, AI/ML, and intelligent document processing. You will own data pipelines and stores, collaborating with ML engineers to ensure reliable, scalable data delivery across structured, semi-structured, and unstructured data in various stores.

Strong Python/SQL and AWS experience are highly valued. The role emphasizes data quality, lineage, orchestration, and operational monitoring, with