Junior Data Engineer: ETL Pipelines & Python for BI

BeaconFire Inc; New Jersey; On-site; USD 62,000 - 80,000; Full time

Job summary

BeaconFire Inc. in New Jersey is seeking a motivated Junior Data Engineer to help build scalable data pipelines and transformation systems. You will work with analysts and engineers to deliver high-quality data solutions that support business insights and decision-making.

You will design and implement ETL/ELT pipelines, extract and clean data from SQL databases, and write Python scripts using Pandas and NumPy to enable robust data processing and automation.

Qualifications

• Master’s Degree in Computer Science, Information Technology, Data Analytics, or related field.
• Proficiency in Python (intermediate level), with exposure to data libraries like Pandas, NumPy.
• Experience working with relational databases and writing SQL queries.
• Strong communication skills — verbal and written.
• Self-motivated and comfortable working in both team and individual settings.

Responsibilities

• Collaborate with analytics and engineering teams to understand and deliver data solutions.
• Design and implement scalable ETL/ELT pipelines.
• Extract, clean, and manipulate data from SQL databases.
• Write and maintain Python scripts for data processing (Pandas, NumPy).
• Develop UDFs, utilities, and reusable code for automation and optimization.
• Participate in testing, troubleshooting, and performance tuning.
• Follow engineering best practices and contribute to improving data quality and reliability.

Skills

Python

SQL

Pandas

NumPy

Education

Master’s Degree in Computer Science, Information Technology, Data Analytics

Tools

Airflow

DBT

AWS

Azure

GCP

Job description

BeaconFire Inc. in New Jersey is seeking a motivated Junior Data Engineer to help build scalable data pipelines and transformation systems. You will work with analysts and engineers to deliver high-quality data solutions that support business insights and decision-making.

You will design and implement ETL/ELT pipelines, extract and clean data from SQL databases, and write Python scripts using Pandas and NumPy to enable robust data processing and automation.