Data Engineer

Power Home Remodeling Group; Aston Township (PA); On-site; USD 110,000 - 160,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Life and disability insurance

Paid vacation & holidays

401(k) retirement plan (matched)

Child care and fertility benefits

Parental leave

Hardware & software stipend

Personal development & conferences

Job summary

Power Home Remodeling Group is seeking a Data Engineer to design, build, and own data pipelines and support a modern lakehouse that powers AI across the business. You’ll influence architecture decisions and help shape standards for data and AI across the company.

You will work on batch and streaming data platforms, optimize production systems, and contribute to retrieval-augmented data workflows while collaborating with analysts and business leaders to deliver reliable datasets and scalable

Qualifications

• 5+ years of data engineering experience with production pipelines.
• Hands-on experience with distributed data processing (e.g., Spark).
• Production experience with data transformation/orchestration tools (dbt, Airflow).
• Strong SQL and Python skills; data modeling foundation.

Responsibilities

• Build batch and real-time data pipelines used daily by the business.
• Lead modernization to real-time data capabilities and scalable architectures.
• Tune, monitor, and Harden production data systems for reliability.
• Build data infrastructure for AI including retrieval, embeddings, and governed access for AI agents.
• Collaborate with analysts and leaders to turn needs into reliable datasets.
• Contribute to code reviews and help set engineering standards.

Skills

5+ years data engineering

Distributed data processing (Spark)

SQL

Python

Data modeling

APIs

Testing

Version control

CI/CD

Written communication

Curiosity & learning AI tools

Tools

Spark

dbt

Airflow

Job description

Data Engineer, Data Platform & AI

Help build the data foundation that powers AI across the business, from the ground up.

Why This Role Is Different

This isn't a seat on a large, established team where the big decisions were made years ago. You'll have real influence here. You'll help shape the architecture choices, standards, and practices that define how the company uses data and AI for years to come.

You’ll work on a modern, open-source-first lakehouse and help take it into its next phase: real-time data and production-grade data for AI. If you've wanted to do meaningful work at the point where data engineering meets generative AI, this is that opportunity.

About The Team

We're a small, high-impact team building the platform that analytics and AI across the business depend on. You'll partner closely with the technical leaders, have real influence over technical direction, and grow your career alongside the platform. We value curiosity, craftsmanship, and clear communication, and we invest in the people who bring them.

What You'll Do

• Build pipelines that matter. Design, build, and own batch and real-time data pipelines that the business relies on every day.
• Lead the shift to real time. Play a hands-on role in modernizing the platform to new tools, architectures, and capabilities as the business grows.
• Make things fast and reliable. Tune and harden production systems so the business can trust its data.
• Build the foundation for AI. Help create the data infrastructure behind intelligent applications, including retrieval, embeddings, and secure, governed access for AI agents.
• Turn ideas into impact. Work with analysts and business leaders to turn their needs into datasets they can depend on.
• Raise the bar. Contribute to code reviews, share knowledge, and help set the engineering standards for a growing team.

What You'll Bring

• 5+ years of data engineering experience, with pipelines you've shipped and supported in production
• Hands-on experience with distributed data processing (such as Spark) and a solid grasp of how to make it perform
• Production experience with modern data transformation and orchestration tools (such as dbt or Airflow)
• Strong SQL and Python skills and a solid foundation in data modeling
• Experience working with data services and APIs
• Good engineering habits, including testing, version control, and CI/CD
• Clear written communication
• Curiosity and a real interest in learning new tools, especially in data for AI

Preferred

• Experience with open table formats or distributed query engines
• Experience with change data capture or streaming technologies
• Hands-on work building retrieval-augmented generation (RAG) or similar AI data workflows
• Exposure to AI agents, agent tooling, or AI evaluation
• Familiarity with containers, orchestration, or infrastructure as code

What's In It For You

• Real impact. Help shape the technology, practices, and direction of a platform the whole business relies on.
• Cutting-edge work. Work hands-on with modern data architecture and production AI, not just talk about them.
• Career growth. Grow with the team as it scales, with room to take on more ownership and leadership.
• Mentorship. Work directly with an experienced team lead who's invested in your development.

Salary & Benefits

• Competitive salary
• Full medical, dental, life and disability insurance plans that can be tailored to your specific needs and the needs of your family
• Ample paid vacation and holiday
• A competitive 401(k) retirement savings program matched by Power
• Subsidized child care and fertility benefits
• Paid parental leave
• All the tech you need - We'll pay for whatever hardware and software you need to work and make sure you're regularly upgraded to the latest versions
• Personal development - Personal development courses, books, & conferences.
• Paid parental leave - When the time comes to welcome a new member of the family, we offer paid parental leave.

Power Home Remodeling Group is an equal opportunity employer, and we are committed to hiring a diverse and talented workforce. If you have a disability or special need that requires accommodation, please submit the accommodation request to [e-mail]