Relocation may be considered for the right candidate.
Salary Range: $130,000–$155,000+ base salary, Negotiable DOE
Eligible for a 10% annual performance bonus with up to a 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 sector to identify a Senior Data Engineer who will help advance and scale a modern enterprise cloud data platform.
This role is designed for an experienced, hands-on data engineer who has built and supported production cloud data environments and is prepared to serve as a technical subject-matter expert across Databricks, Snowflake, Python, SQL, and the Microsoft Azure ecosystem.
The Senior Data Engineer will design and maintain scalable data pipelines, optimize Databricks environments, strengthen data governance, automate modern engineering workflows, and improve the reliability, performance, and cost efficiency of the organization’s cloud data platform. The position will work closely with Data Strategy, Finance, Operations, Analytics, and business leadership to translate complex business needs into sustainable technical solutions.
The immediate focus is enterprise data infrastructure, data warehouse development, Databricks integration, governance, and platform scalability. While advanced analytics and AI-related initiatives may become part of the organization’s longer-term roadmap, this position is primarily focused on building and maturing the core cloud data foundation.
Required Skills & Qualifications
Minimum of 5 years of professional Data Engineering, Cloud Data Engineering, or closely related experience
Demonstrated, hands-on experience developing and supporting Databricks in a production environment
Strong professional experience with Snowflake cloud data platforms
Advanced development experience with Python, PySpark, and SQL
Proven experience designing, developing, and supporting scalable ETL/ELT pipelines
Strong understanding of cloud data architecture, preferably within Microsoft Azure
Experience with enterprise data warehousing, relational databases, schema design, data modeling, and performance optimization
Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, or a related technical discipline
Must be authorized to work in the United States without current or future employer sponsorship
Preferred Skills & Qualifications
Experience with Azure Data Factory, Azure Data Lake Storage, Azure Synapse Analytics, and Azure DevOps
Hands-on experience with Delta Lake, including data reliability, performance, optimization, and versioning
Experience implementing or supporting Databricks Unity Catalog and enterprise data-governance practices
Experience developing automated CI/CD pipelines for data engineering workflows
Experience with workflow orchestration through Databricks Jobs, Azure Data Factory pipelines, or similar tools
Experience monitoring and optimizing Databricks clusters for performance, reliability, scalability, and cost efficiency
Familiarity with Azure Log Analytics, Databricks monitoring tools, or custom platform-performance dashboards
Exposure to Power BI, Tableau, or other enterprise reporting and data-visualization tools
Working knowledge of Scala, Pandas, Linux, Bash, Docker, or related engineering technologies
Experience supporting financial, operational, ERP, manufacturing, supply-chain, construction, or enterprise business data
Ability to communicate technical information clearly to both technical and non-technical stakeholders, including business and executive leadership
Day-to-Day Responsibilities
Design, develop, deploy, and maintain scalable cloud-based data pipelines within the Databricks environment
Build and optimize enterprise ETL/ELT workflows using Python, PySpark, SQL, and modern cloud technologies
Monitor and optimize Databricks clusters to improve performance, scalability, reliability, resource utilization, and cost efficiency
Implement and maintain Delta Lake architecture to support reliable data storage, versioning, governance, and performance
Integrate Databricks with Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, Azure DevOps, and other Azure services
Develop and maintain automated CI/CD pipelines supporting data engineering deployments and workflow automation
Design monitoring and observability solutions using Databricks tools, Azure Log Analytics, and custom dashboards
Support enterprise data governance, access controls, lineage, and cataloging through Databricks Unity Catalog
Partner with Finance, Operations, Analytics, technology teams, and business stakeholders to convert requirements into scalable data solutions
Troubleshoot complex production data issues and improve platform availability, data quality, and operational stability
Help establish engineering standards, reusable frameworks, documentation, and cloud data-platform best practices
Provide technical leadership and mentorship while helping shape the long-term direction and maturity of the enterprise data ecosystem
Physical and Environment Requirements
This position operates primarily in a professional hybrid office environment. Physical expectations and working conditions may include sitting or standing for extended periods, working at a computer, participating in virtual and in-person meetings, and communicating regularly with technical and business stakeholders.
The role requires the ability to manage multiple priorities, analyze complex technical issues, collaborate across functional teams, and present technical information to audiences with varying levels of technical expertise.
Company Benefits & Culture
This opportunity offers the stability of an established, growth-oriented organization combined with the technical challenge of helping build and scale a modern enterprise cloud data platform.
Competitive base salary based on experience
10% annual performance bonus with up to a 2x multiplier opportunity
Comprehensive medical, dental, and vision benefits
401(k) plan with company match
Paid time off and company holidays
Hybrid work flexibility
Relocation consideration for qualified candidates
High visibility across Data Strategy, Finance, Operations, Analytics, and business leadership
Opportunity to influence enterprise cloud architecture, engineering standards, governance, and platform strategy
Long-term professional growth within an organization actively investing in technology, analytics, and data-driven decision-making
Collaborative environment that values analytical thinking, creativity, technical ownership, and cross-functional partnership