Data Platforms Engineer — Real-Time Insights

CLM Dallas Chapter; Boston (MA); On-site; USD 110,000 - 160,000; Full time

Benefits offered by this job

Comprehensive benefits

Workplace flexibility

Professional development opportunities

Employee Resource Groups

Job summary

CLM Dallas Chapter is seeking a capable Full Stack Engineer to build and maintain the DataForge data factory platform, supporting the Technology Data Office and a range of data products. You will contribute to scalable pipelines and real-time intelligence for business and technology leaders.

Work with a cross-functional Agile team, focusing on React, Node.js, and cloud platforms. The role emphasizes CI/CD, RESTful services, and ideally Snowflake and DBT experience to accelerate data-driven

Qualifications

• Requires a bachelor's degree and at least 3 years of full stack engineering experience with a focus on React, Node.js, and cloud platforms.
• Candidates must be proficient in CI/CD, RESTful services, and preferably have experience with Snowflake and DBT.

Responsibilities

• Build and maintain the DataForge data factory platform to support the Technology Data Office and various data products.
• Collaborate with engineering teammates in an agile environment to deliver real-time intelligence for business and technology leaders.

Skills

React

TypeScript

JavaScript

Node.js

AWS

S3

Cloud Foundry

GitHub Actions

RESTful APIs

CI/CD

DevOps

Snowflake

DBT

Airflow

Scrum

Full Stack Engineering

Education

Bachelor's degree

Tools

Snowflake

DBT

Airflow

Job description

CLM Dallas Chapter is seeking a capable Full Stack Engineer to build and maintain the DataForge data factory platform, supporting the Technology Data Office and a range of data products. You will contribute to scalable pipelines and real-time intelligence for business and technology leaders.

Work with a cross-functional Agile team, focusing on React, Node.js, and cloud platforms. The role emphasizes CI/CD, RESTful services, and ideally Snowflake and DBT experience to accelerate data-driven