Remote Junior Big Data Engineer for AI Pipelines

Drivenintelligence; United States; Hybrid; USD 70,000 - 100,000; Full time

Job summary

Drivenintelligence is seeking a Junior Big Data Engineer to help build and maintain modern data pipelines and analytics-ready datasets for AI-enabled business systems. You will work closely with senior engineers to learn practical data engineering skills and apply them to real-world use cases in a remote/hybrid US setting.

This early-career role focuses on Python/SQL, batch and streaming pipelines, data quality checks, and documentation to ensure reliable data flows for analytics, automation,

Qualifications

• Hands-on experience with Python and SQL through coursework, projects, internships, or professional work.
• Familiarity with ETL/ELT concepts, data modeling basics, and cloud data platforms.
• Interest in big data tools such as Spark, PySpark, Databricks, Snowflake, BigQuery, or similar platforms.
• Comfort learning new systems quickly and asking clear questions when requirements are ambiguous.
• Strong attention to detail and a bias toward clean, maintainable work.

Responsibilities

• Build and maintain batch and streaming data pipelines using Python, SQL, and cloud data tools.
• Support data ingestion, transformation, validation, and quality checks across structured and semi-structured sources.
• Work with senior engineers to design analytics-ready datasets, feature pipelines, and reporting layers.
• Document data flows, assumptions, and operational handoffs so client teams can maintain what we build.
• Troubleshoot pipeline failures, data quality issues, and performance bottlenecks.

Skills

Python

SQL

ETL/ELT concepts

Cloud data platforms

Big data tools (Spark, PySpark, Databr

Learning new systems

Detail-oriented, clean code

Tools

Airflow

Dagster

Prefect

dbt

Job description

Drivenintelligence is seeking a Junior Big Data Engineer to help build and maintain modern data pipelines and analytics-ready datasets for AI-enabled business systems. You will work closely with senior engineers to learn practical data engineering skills and apply them to real-world use cases in a remote/hybrid US setting.

This early-career role focuses on Python/SQL, batch and streaming pipelines, data quality checks, and documentation to ensure reliable data flows for analytics, automation,