Senior Data Engineer - Remote Cloud Pipelines

Plain Concepts Group; United States; Remote; USD 90,000 - 150,000; Full time

Benefits offered by this job

Fully free health insurance, with a co

Job summary

Plain Concepts is expanding its data-focused team. We’re seeking a passionate Data Engineer to design and deploy data-powered solutions for diverse clients across our international squad. Train, implement, and scale cutting-edge technologies while owning projects from start to finish.

Remote-friendly with optional office presence and a flexible 35-hour work week. You’ll work with Python/Scala, Spark, and cloud platforms (Azure/AWS), build scalable ETL pipelines, and contribute to best practices,

Qualifications

• At least 4 years of experience in data engineering.
• Strong experience with Python or Scala and Spark.
• Solid experience in Cloud platforms (Azure or AWS).
• Experience working with Snowflake.
• Hands-on experience building data pipelines (CI/CD).
• Experience with testing (unit, integration, etc.).
• Experience with DBT (Data Build Tool) for data transformation and modelling. Implement data transformation workflows using DBT (core/cloud).

Responsibilities

• Participating in the design and development of data solutions for challenging projects.
• Develop projects from scratch with minimal supervision and strong team collaboration.
• Be a key player in fostering best practices, clean, and reusable code.
• Develop ETLs using Spark (Python/Scala).
• Work on cloud-based projects (Azure/AWS).
• Build scalable pipelines using a variety of technologies.

Skills

Python

Scala

Spark

SQL

NoSQL

Azure

AWS

DBT

CI/CD

English

Tools

Snowflake

Job description

Plain Concepts is expanding its data-focused team. We’re seeking a passionate Data Engineer to design and deploy data-powered solutions for diverse clients across our international squad. Train, implement, and scale cutting-edge technologies while owning projects from start to finish.

Remote-friendly with optional office presence and a flexible 35-hour work week. You’ll work with Python/Scala, Spark, and cloud platforms (Azure/AWS), build scalable ETL pipelines, and contribute to best practices,