Data Engineer – ETL Pipelines & BI

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

Job summary

BeaconFire Inc. seeks a data-centric professional to design and maintain data integrations, reporting pipelines, and transformation systems in California. You will collaborate with analytics to create reliable data solutions and implement scalable ETL/ELT processes.

The role emphasizes strong Python skills, experience with Numpy/Pandas, and proficiency in SQL databases. Excellent communication and teamwork are essential as you address data challenges and contribute to data quality.

Qualifications

• Master’s degree in Computer Science/IT/Data Analytics or related discipline.
• Proficient in Python; experience with data processing using Numpy and Pandas.
• Experience with relational databases (SQL Server, Oracle, MySQL).
• Strong written and verbal communication; able to work independently or in a team.
• Passion for data and eagerness to learn.

Responsibilities

• Collaborate with analytics team to design reliable data solutions.
• Design and implement scalable ETL or ELT processes to support data demand.
• Perform data extraction, manipulation, and production from database tables.
• Build utilities and frameworks to enable data flow patterns.
• Develop automated unit tests and participate in integration testing.
• Address operational and performance issues with engineering teams.
• Ensure quality solutions adhere to engineering best practices.

Skills

Passion for data

Python

SQL

Communication skills

Teamwork

Education

Master’s degree in CS/IT/Data Analytics

Tools

Numpy

Pandas

SQL Server

Oracle

MySQL

Job description

BeaconFire Inc. seeks a data-centric professional to design and maintain data integrations, reporting pipelines, and transformation systems in California. You will collaborate with analytics to create reliable data solutions and implement scalable ETL/ELT processes.

The role emphasizes strong Python skills, experience with Numpy/Pandas, and proficiency in SQL databases. Excellent communication and teamwork are essential as you address data challenges and contribute to data quality.