Senior Data Engineer

Matrix Global•Kansas City, MO

About The Position

We are seeking an accomplished Senior Data Engineer with extensive experience in data engineering, ETL development, and semantic data modeling. This role is responsible for supporting and enhancing enterprise data pipelines, optimizing analytical data models, and delivering scalable business intelligence solutions. The ideal candidate combines strong technical expertise in SQL Server-based data ecosystems with hands-on experience building high-performing semantic models and supporting enterprise reporting platforms. This position requires a balance of production support, data architecture, performance optimization, stakeholder engagement, and mentoring of junior team members.

Requirements

Bachelor's degree in computer science, Information Systems, Engineering, Data Analytics, or a related field.
8+ years of experience in data engineering, ETL development, data warehousing, and analytics solutions.
Advanced expertise in SQL development, database design, query optimization, and performance tuning.
Strong experience with ETL/ELT development and enterprise data integration platforms.
Proven experience supporting production data environments and troubleshooting complex data issues.
Hands-on experience with semantic modeling, analytical data structures, and business intelligence platforms.
Strong knowledge of dimensional modeling, star schema design, and data warehouse architecture.
Experience developing and optimizing analytical calculations and reporting datasets.
Excellent problem-solving, analytical, and root-cause analysis skills.
Strong written and verbal communication skills with the ability to work across technical and business teams.

Nice To Haves

Experience with cloud-based data integration and orchestration platforms.
Familiarity with modern cloud data warehouses and analytics platforms.
Experience working within cloud environments and data architecture frameworks.
Knowledge of scripting and automation tools such as Python, PowerShell, or similar technologies.
Experience with multiple relational database platforms and data processing technologies.
Familiarity with enterprise data catalog and metadata management solutions.
Understanding of business functions such as Finance, Human Resources, Operations, Project Costing, or similar domains.
Experience validating and reconciling data across analytical and operational systems.
Strong quality assurance and data governance mindset.

Responsibilities

Monitor, support, and enhance enterprise data pipelines to ensure data accuracy, reliability, and availability.
Design, develop, maintain, and optimize ETL/ELT processes and workflows.
Troubleshoot data quality issues, performance bottlenecks, and production incidents while minimizing business impact.
Manage and optimize enterprise job scheduling and workflow automation platforms.
Partner with cross-functional teams to resolve data-related issues, perform root-cause analysis, and implement long-term corrective actions.
Maintain technical documentation, data flow diagrams, operational procedures, and support materials.
Ensure data governance, operational continuity, and adherence to best practices.
Design, develop, and maintain enterprise semantic and analytical data models.
Support migration and modernization of legacy analytical models into modern BI platforms.
Build scalable semantic models that enable self-service analytics and reporting.
Develop and optimize SQL queries, analytical calculations, and transformation logic to support reporting and business intelligence requirements.
Collaborate with engineering teams to design schemas, tables, and structures that maximize reporting and query performance.
Document business rules, data lineage, transformations, and metadata.
Monitor and support deployed analytical models, ensuring optimal performance and availability.
Apply dimensional modeling principles and data warehousing best practices.
Design and maintain fact and dimension structures that support enterprise reporting needs.
Ensure consistency and accuracy across reporting, analytical, and operational data layers.
Work closely with reporting and analytics teams to improve usability and performance of BI solutions.
Partner with business and technical stakeholders to understand requirements and translate them into scalable data solutions.
Support delivery of data products and reporting capabilities aligned with organizational objectives.
Provide guidance and mentorship to junior data engineers and analysts.
Promote engineering standards, documentation practices, and technical excellence across the team.
Research, evaluate, and recommend emerging technologies, tools, and methodologies to improve data engineering capabilities.