$85,000–$115,000 base salary + 10% annual bonus with 2x multiplier opportunity
Employment Type:
Direct Hire | Full-Time
Job Summary:
MS Companies is partnering with a confidential, industry-leading organization in the infrastructure and construction materials space to identify a Data Engineer to support the design, development, and implementation of a modern cloud-based data platform.
This role is ideal for a hands-on data professional who enjoys building scalable data pipelines, working with modern cloud technologies, and transforming complex enterprise data into actionable business insights. The Data Engineer will work closely with Finance, Operations, technical teams, and business stakeholders to support enterprise reporting, analytics, decision intelligence, and future AI/ML initiatives.
The ideal candidate will bring hands-on experience with Databricks, Snowflake, Python, SQL, and cloud-based data engineering, along with strong communication and presentation skills. Candidates with 1–3 years of Data Engineering experience are encouraged to apply; candidates with 3–5 years of experience may be considered for a Data Engineer II-level role.
Required Skills & Qualifications
1–3 years of Data Engineering or Cloud Data Engineering experience; 3–5 years may be considered for Data Engineer II
Hands-on experience with Databricks, Snowflake, and Python
Strong SQL development skills
Experience building and supporting ETL/ELT data pipelines
Experience working in Azure or another cloud-based data environment
Strong understanding of database design, schema optimization, and data modeling
Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field
Must be authorized to work in the U.S. without sponsorship
Preferred Skills & Qualifications
Experience with Azure Data Factory, Azure Data Lake Storage, or Azure DevOps
Experience with Delta Lake architecture and Databricks optimization
Experience with PySpark, Pandas, or similar Python data engineering frameworks
Experience with CI/CD pipelines and workflow automation
Working knowledge of Linux, Bash, or Docker
Experience with workflow orchestration tools such as Databricks Jobs or Azure Data Factory
Exposure to Power BI, Tableau, or other enterprise reporting tools
Experience supporting ERP, financial, manufacturing, supply chain, or operations data environments
Day-to-Day Responsibilities
Design, develop, and maintain scalable cloud-based data pipelines
Build, optimize, and support Databricks environments, clusters, and workflows
Develop ETL/ELT processes using Python, SQL, and modern cloud technologies
Support Delta Lake architecture and cloud data warehouse initiatives
Integrate Databricks with Azure services, including Azure Data Factory, ADLS, and Azure DevOps
Build and maintain CI/CD pipelines supporting modern data engineering workflows
Monitor, troubleshoot, and optimize data platform performance, reliability, scalability, and cost efficiency
Partner with Finance, Operations, technical teams, and business stakeholders to deliver data-driven insights and scalable business solutions
Physical and Environment Requirements
This role operates in a professional hybrid office environment. Physical expectations may include sitting for extended periods, working at a computer, participating in meetings, collaborating with cross-functional teams, and communicating technical information to both technical and non-technical stakeholders.
Company Benefits & Culture
Competitive base salary with annual performance-based bonus opportunity
10% annual bonus with 2x multiplier potential
Comprehensive health, dental, and vision benefits
401(k) with company match
Hybrid work flexibility
Opportunity to help build and scale a modern enterprise cloud data platform
Strong cross-functional exposure across Finance, Operations, Analytics, and leadership teams
Long-term growth opportunity within a stable, growing organization investing in technology, innovation, and data-driven decision-making