Data Engineer

Overview

Build and maintain scalable multi-tenant data pipelines and platforms on AWS.

Key Responsibilities

• data extraction
• data lakes
• reporting db
• predictive modeling
• pipeline monitoring
• unit tests

Tasks

Develops unit tests and uses version control (git). Travel to customer locations including overnight, business air travel, and car rental. 7. Work closely within the team to prepare data for predictive and prescriptive modeling. Adheres to code quality standards. 8. Evaluate tools and frameworks and articulate the considerations in buy vs. build options. 6. Within a cross-functional agile team, collaborate with related roles and in alignment with Product, Design, Architecture, and Tech Engineering (operations). 5. Embody both documentation-driven and test-driven development and apply design principles. 4. Implement monitoring for pipeline performance and other pipeline metrics. 9. Write high quality, testable code. Develop a testing strategy and build appropriate pipelines to enable rapid feedback. -Data extraction and preparation -Building and maintaining data lakes -Choosing and implementing reporting databases

Requirements

• python
• aws
• ci/cd
• airflow
• agile
• bachelor

What You Bring

Experienced in participating in peer code reviews. Knowledgeable with cloud tech stacks (e.g. AWS: S3, Lake Formation, Glue, Athena. Redshift). Bachelor or Master’s Degree in Computer Science, Computer Engineering, Electrical Engineering, Management Information Systems, or related field preferred. Experience as a software engineer with the bulk - or at least most recent - of those years spent in a modern development environment with CI/CD, source control management, and containerization. Well-experienced in working in Agile shop. DevOps, Continuous Integration and Continuous Delivery experience. Ability to work with large data sets. Experience with a handful of modern data pipeline tools and the ability to recommend the right tool for the job (Meltano, Singer, dbt, Airflow). Experience curating data from multiple sources and devising strategy for use of legacy data stores. Experience creating recommendations for tools, frameworks, and component builds. Knowledge of building, scaling, and securing multi-tenant environment. -Python (preferably in AWS) -Scripting (Unix/Windows) -Scalable data delivery -Data Visualization -Programming Languages commonly used in data engineering such as;

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Benefits

Normal office environment with use of computers and telephone systems; no unusual physical demands.

About Dmsi Software

-Family‑owned and fiercely customer‑focused, they’ve grown while keeping support tailored to building‑materials businesses. -Flagship products include Agility ERP, Frameworks ERP, and DMSi Log—designed for distributors, dealers, millwork, and lumber operations. -Typical projects involve end‑to‑end system rollouts: inventory, POS, job‑site delivery, accounting, and e‑commerce portals. -They serve hundreds of dealers and thousands of users across North America, integrating modern cloud, mobile, and API‑based tech.

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