Remote AI-Driven Data Engineer for Cloud Platform

Page Mechanical Group, Inc.; Northern (KY); Hybrid; USD 100,000 - 170,000; Full time

Job summary

Gigapower LLC is seeking a Data Engineer to architect and build a cloud-based data platform that powers analytics, automation, and AI-driven applications. You will own data models, ingestion pipelines, and governance across diverse data sources while ensuring secure, scalable access for analytics and AI workloads.

The role requires hands-on development in a fast-paced environment, strong SQL/data modeling, and experience with cloud data warehouses and Python.

Qualifications

• Bachelor’s degree or equivalent in CS/IS/Data Eng.
• 3–6 years in data engineering building warehouses and data marts.
• Strong SQL and data modeling skills.
• Experience with cloud data platforms (Snowflake/BigQuery/Redshift) and Python.
• Geospatial data experience; Azure cloud familiarity.

Responsibilities

• Design scalable cloud data models integrating operational, financial, engineering, and field data.
• Develop data ingestion, transformation, orchestration, and monitoring across sources.
• Create data warehouses, marts, and analytical datasets for reporting and AI workloads.
• Model geospatial data and support RAG, AI search, ML apps.
• Maintain data quality, governance, lineage, and confidentiality.
• Collaborate with IT/Sec/Infra for access controls and reliability.
• Translate operational needs into scalable data solutions with stakeholders.
• Monitor performance and cost efficiency of the data platform.
• Leverage AI-powered tools to improve productivity and outcomes.

Skills

SQL

Data modeling

Python

Geospatial data

Stakeholder communication

Problem solving

Education

Bachelor's degree in CS/IS/Data Eng or related

Tools

Snowflake

BigQuery

Redshift

Azure Data Factory

Airflow

Dagster

Esri ArcGIS

Azure

Job description

Gigapower LLC is seeking a Data Engineer to architect and build a cloud-based data platform that powers analytics, automation, and AI-driven applications. You will own data models, ingestion pipelines, and governance across diverse data sources while ensuring secure, scalable access for analytics and AI workloads.

The role requires hands-on development in a fast-paced environment, strong SQL/data modeling, and experience with cloud data warehouses and Python.