Senior Data Engineer - Remote Data Pipelines & AI

Pantheon Data LLC.; Reston, Northern (VA, KY); Hybrid; USD 140,000 - 160,000; Full time

Benefits offered by this job

SmartBenefits program

Tuition assistance

Job summary

Pantheon Data LLC is seeking a hands-on Data Engineer to design, build, and operate data foundations for analytics, AI/ML, and document processing. You will handle ingestion, orchestration, validation, and delivery across structured, semi-structured, and unstructured data, while collaborating with ML and software teams.

Ideal candidates have strong Python and SQL skills, experience with data modeling, batch and event-driven pipelines, and a pragmatic approach to reliability and observability.

Qualifications

• Bachelor's degree in CS/Engineering from ABET-accredited university.
• 5+ years of hands-on data engineering or closely related experience.
• Strong Python and SQL skills with production-ready code.
• Experience with data pipelines, ETL/ELT, and orchestration.
• Familiarity with AWS data services and data governance concepts.

Responsibilities

• Design, build, and maintain reliable data pipelines for diverse data sources.
• Develop Python-based workflows for ingestion, normalization, validation, and transformation.
• Work with SQL and relational stores to support transactional and analytical workloads.
• Design data models and storage patterns for OLTP/OLAP and unstructured data.
• Implement orchestration and scheduling with Airflow, Step Functions, Dagster, or similar.

Skills

Python

SQL

Data modeling

ETL/ELT

Airflow

Git

Communication

Distributed systems

Education

ABET-accredited CS/Engineering degree

Tools

Docker

OpenSearch

Spark

Job description

Pantheon Data LLC is seeking a hands-on Data Engineer to design, build, and operate data foundations for analytics, AI/ML, and document processing. You will handle ingestion, orchestration, validation, and delivery across structured, semi-structured, and unstructured data, while collaborating with ML and software teams.

Ideal candidates have strong Python and SQL skills, experience with data modeling, batch and event-driven pipelines, and a pragmatic approach to reliability and observability.