Sr Data Engineer

As part of our evolving Product strategy, DMSi seeks to expand our footprint of usable data at scale. DMSi creates and operates technology solutions to support the Building Materials industry. We want to offer uses for our data which serve future product initiatives, customer and business self-service needs, and broader industry needs. All the while, we intend to produce a cloud-based, multi-tenant, data environment which is responsive to the evolving nature of the data landscape and the industry.

As our Senior Data Engineer, you'll own the data pipeline that powers DMSi's next generation of data products—from enterprise data access to AI-powered analytics, building, scaling, and evolving our data pipeline, and shipping products that building materials professionals will use every day.

You'll work within DMSi's broader architectural ecosystem, collaborating closely with Systems Engineering, Information Security, and the Architecture teams. As the expert voice for data, you'll advocate for best practices and drive execution within those guardrails. 

 RESPONSIBILITIES AND DUTIES:

1. Own the Data Pipeline
   • Design, build, and evolve the data pipelines that power DMSi's data products—working within our established stack (PostgreSQL, Kafka, dbt).
   • Drive technical decisions for scalable and performant data extraction, transformation, and delivery—selecting tools, evaluating build vs. buy, and establishing frameworks and processes.
   • Establish data governance standards and quality assurance practices.
   • Serve as DMSi's internal expert on data engineering best practices.
2. Ship Products 
   • Launch multiple data products, including enterprise data access (PostgreSQL), event streaming (Kafka), and in-app analytics.
   • Build production-ready pipelines that deliver customer data reliably at scale in a multi-tenant environment.
   • Create a foundational data infrastructure to support AI and machine learning capabilities across DMSi's product portfolio.
   • Partner with Product to iterate quickly from customer feedback to deployed improvements.
3. Collaborate Across Teams 
   • Work closely with Systems Engineering and Architecture to ensure data infrastructure integrates seamlessly with DMSi's broader technical operations.
   • Partner with Information Security to implement data security, access controls, and compliance requirements.
   • Provide technical leadership and mentorship to Data Engineers on the team.
   • Conduct code reviews that elevate quality and transfer knowledge across the organization.

KNOWLEDGE, SKILLS, AND ABILITIES:
5+ years of hands-on data engineering experience, with at least 2 years in a senior or lead capacity.
Deep expertise in SQL designing schemas, optimizing queries, and troubleshooting performance issues confidently.
Production experience building and maintaining data pipelines using modern tools (dbt strongly preferred; experience with Airflow, Meltano, Singer, or similar also valuable).
Strong Python skills for data processing, automation, and scripting.
Cloud infrastructure experience (AWS and GCP preferred: S3, Glue, Athena, Redshift, Lake Formation).
DevOps fluency—CI/CD pipelines, containerization, and infrastructure-as-code are familiar territory.
Collaborative mindset and strong communication skills.
Background in building data products or platforms (not just internal analytics).
Exposure to machine learning pipelines or feature stores.

EDUCATION AND EXPERIENCE: 
Bachelor's or Master’s Degree in Computer Science, Computer Engineering, Electrical Engineering, Management Information Systems, or related field preferred.
Well-experienced in working in Agile shop.

WORK ENVIRONMENT AND PHYSICAL DEMANDS:
Normal office environment with use of computers and telephone systems; no unusual physical demands.
Travel to customer locations including overnight, business air travel, and car rental.