Data Analytics Engineer Visa Sponsorship Jobs in Missouri
Missouri's data analytics engineer market centers on Kansas City and St. Louis, where financial services firms like Edward Jones and Centene Corporation, along with major healthcare and logistics employers, actively hire for data pipeline and analytics infrastructure roles. Companies in these sectors have established H-1B visa sponsorship track records, making Missouri a realistic target for international candidates.
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Data Analytics Engineer
Job Description Summary
As the Data & Analytics Engineer, you will build and maintain scalable data pipelines, data models, and organized datasets that enable reliable analytics, reporting, and business decision-making across strategic client accounts. You will translate business and data requirements into durable technical solutions, with hands-on ownership of data ingestion, transformation, integration, quality, and preparation for downstream business intelligence and visualization.
As a member of Cushman & Wakefield’s Portfolio Advisory Group, the Data & Analytics Engineer will be dedicated to one or more of Cushman & Wakefield’s most dynamic client accounts. In this role, you will collaborate closely with peers and the account team to support a client's strategic real estate vision. The Data & Analytics Engineer will embody our team philosophy “Client First, Insight Always, Execution Excellence”, ensuring every deliverable reflects the team’s commitment to innovation, collaboration, and measurable impact.
This role will primarily:
- Build and maintain scalable ETL/ELT pipelines and data structures that integrate information from multiple sources and make trusted data accessible for analytics and reporting.
- Transform, model, validate, and organize data so stakeholders can rely on consistent datasets for dashboards, visualization, reporting, and decision support.
- Translate client and business requirements into practical data engineering solutions using Databricks or Microsoft Fabric, SQL, and related technologies.
- Improve data accessibility, reliability, and delivery efficiency through automation, data quality controls, documentation, and technical process improvement.
Success in this role looks like:
- Data pipelines consistently deliver reliable, accurate, and accessible datasets for downstream analytics and stakeholder-facing solutions.
- Data models and transformations support scalable reporting and reduce dependence on manual data preparation.
- Data quality controls and documentation improve confidence, consistency, and usability across analytics outputs.
- Business requirements are translated into maintainable technical solutions that stakeholders and analytics teams can effectively use.
Key Responsibilities
Data Engineering & Pipeline Development
- Design, develop, maintain, and troubleshoot ETL/ELT pipelines that ingest, transform, validate, and deliver data from multiple sources into centralized data platforms.
- Build and optimize data processing workflows using Databricks or Microsoft Fabric to support scalable analytics and reporting requirements.
- Automate and improve recurring data processes to strengthen pipeline performance, reliability, and operational efficiency.
Data Modeling & Integration
- Develop and maintain structured data models, including dimensional models where appropriate, that support business intelligence, dashboards, reporting, and analytical use cases.
- Integrate and organize data from multiple source systems into accessible, consistent datasets designed for downstream consumption.
- Prepare and transform data to enable visualization, reporting, business analysis, and stakeholder decision-making.
Data Quality, Governance & Reliability
- Implement data validation, quality controls, governance practices, and documentation that improve the accuracy and reliability of analytical data.
- Identify and resolve data issues, inconsistencies, and pipeline failures that could affect reporting quality or stakeholder confidence.
- Document data structures, transformations, business rules, and technical processes to support transparency, maintainability, and consistent use.
Business Intelligence & Data Accessibility
- Develop datasets and data structures that enable dashboards, visualization, reporting, and other stakeholder-facing analytical solutions.
- Support dashboard and visualization development using Power BI or comparable business intelligence platforms.
- Improve how business users and analytics teams access and use trusted data for recurring reporting and decision support.
Stakeholder Partnership & Continuous Improvement
- Partner with client stakeholders, analytics teams, business leaders, and technical partners to gather requirements and translate business needs into technical solutions.
- Communicate technical concepts, data limitations, dependencies, and delivery progress clearly to technical and nontechnical stakeholders.
- Identify and implement opportunities to automate data workflows, reduce manual processes, improve maintainability, and support geospatial or location-intelligence requirements where applicable.
Qualifications
Must-Have Requirements
- Approximately 3–4+ years of relevant experience in data engineering, analytics engineering, business intelligence, or a closely related field.
- Hands-on experience with Databricks or Microsoft Fabric, including practical experience developing data solutions rather than solely consuming platform outputs.
- Demonstrated experience building, maintaining, and troubleshooting ETL/ELT pipelines.
- Strong working knowledge of SQL, data transformation, data integration, and data modeling.
- Experience preparing structured datasets for business intelligence, dashboards, reporting, visualization, or stakeholder consumption.
- Understanding of data quality, validation, governance, and data-management practices.
- Demonstrated ability to translate business requirements into technical deliverables and collaborate effectively with business, client, and technical stakeholders.
Preferred Experience
- Experience working with both Databricks and Microsoft Fabric.
- Experience with Lakehouse architecture, Delta Lake, Unity Catalog, or comparable modern data-platform technologies.
- Experience using Python or another programming language for data engineering or automation.
- Experience developing or supporting solutions in Power BI, Tableau, or comparable visualization platforms.
- Experience with dimensional modeling, data warehousing, enterprise reporting, or enterprise data-management frameworks.
- Experience with Esri/ArcGIS, geospatial analytics, mapping, or location intelligence.
- Experience supporting enterprise clients, consulting engagements, client-facing analytics initiatives, or AI-enabled analytics technologies.
Technology & Tools
- Databricks and/or Microsoft Fabric
- SQL and ETL/ELT development technologies
- Data modeling, integration, and modern data-platform technologies
- Python
- Power BI or comparable business intelligence and visualization tools
- Delta Lake, Unity Catalog, or related Lakehouse technologies
- Esri/ArcGIS and geospatial analytics tools, where applicable
- AI-enabled analytics and automation solutions
Capabilities
- Technical problem-solving and structured analytical thinking.
- Ability to translate business requirements into scalable technical solutions.
- Strong attention to data accuracy, reliability, maintainability, and usability.
- Clear communication of technical concepts to business and client stakeholders.
- Organization and prioritization across concurrent technical requirements and projects.
- Cross-functional collaboration across business, analytics, and technical teams.
- Continuous improvement mindset focused on automation, scalability, data accessibility, and measurable business impact.
Education
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Data Analytics, or a related field preferred; equivalent relevant professional experience may be considered.
Cushman & Wakefield also provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health, vision, and dental insurance, flexible spending accounts, health savings accounts, retirement savings plans, life, and disability insurance programs, and paid and unpaid time away from work. In addition to a comprehensive benefits package, Cushman and Wakefield provide eligible employees with competitive pay, which may vary depending on eligibility factors such as geographic location, date of hire, total hours worked, job type, business line, and applicability of collective bargaining agreements.
The compensation that will be offered to the successful candidate will depend on factors such as whether the position is covered by a collective bargaining agreement, the geographic area in which the work will be performed, market pay rates in that area, and the candidate’s experience and qualifications.
The company will not pay less than minimum wage for this role.
The compensation for the position is: $106,250.00 - $125,000.00
Cushman & Wakefield is an Equal Opportunity employer to all protected groups, including protected veterans and individuals with disabilities. Discrimination of any type will not be tolerated.
In compliance with the Americans with Disabilities Act Amendments Act (ADAAA), if you have a disability and would like to request an accommodation in order to apply for a position at Cushman & Wakefield, please call the ADA line at 1-888-365-5406 or email Accommodations@cushwake.com. Please refer to the job title and job location when you contact us.
Job Title
Data Analytics Engineer
Job Description Summary
As the Data & Analytics Engineer, you will build and maintain scalable data pipelines, data models, and organized datasets that enable reliable analytics, reporting, and business decision-making across strategic client accounts. You will translate business and data requirements into durable technical solutions, with hands-on ownership of data ingestion, transformation, integration, quality, and preparation for downstream business intelligence and visualization.
As a member of Cushman & Wakefield’s Portfolio Advisory Group, the Data & Analytics Engineer will be dedicated to one or more of Cushman & Wakefield’s most dynamic client accounts. In this role, you will collaborate closely with peers and the account team to support a client's strategic real estate vision. The Data & Analytics Engineer will embody our team philosophy “Client First, Insight Always, Execution Excellence”, ensuring every deliverable reflects the team’s commitment to innovation, collaboration, and measurable impact.
This role will primarily:
- Build and maintain scalable ETL/ELT pipelines and data structures that integrate information from multiple sources and make trusted data accessible for analytics and reporting.
- Transform, model, validate, and organize data so stakeholders can rely on consistent datasets for dashboards, visualization, reporting, and decision support.
- Translate client and business requirements into practical data engineering solutions using Databricks or Microsoft Fabric, SQL, and related technologies.
- Improve data accessibility, reliability, and delivery efficiency through automation, data quality controls, documentation, and technical process improvement.
Success in this role looks like:
- Data pipelines consistently deliver reliable, accurate, and accessible datasets for downstream analytics and stakeholder-facing solutions.
- Data models and transformations support scalable reporting and reduce dependence on manual data preparation.
- Data quality controls and documentation improve confidence, consistency, and usability across analytics outputs.
- Business requirements are translated into maintainable technical solutions that stakeholders and analytics teams can effectively use.
Key Responsibilities
Data Engineering & Pipeline Development
- Design, develop, maintain, and troubleshoot ETL/ELT pipelines that ingest, transform, validate, and deliver data from multiple sources into centralized data platforms.
- Build and optimize data processing workflows using Databricks or Microsoft Fabric to support scalable analytics and reporting requirements.
- Automate and improve recurring data processes to strengthen pipeline performance, reliability, and operational efficiency.
Data Modeling & Integration
- Develop and maintain structured data models, including dimensional models where appropriate, that support business intelligence, dashboards, reporting, and analytical use cases.
- Integrate and organize data from multiple source systems into accessible, consistent datasets designed for downstream consumption.
- Prepare and transform data to enable visualization, reporting, business analysis, and stakeholder decision-making.
Data Quality, Governance & Reliability
- Implement data validation, quality controls, governance practices, and documentation that improve the accuracy and reliability of analytical data.
- Identify and resolve data issues, inconsistencies, and pipeline failures that could affect reporting quality or stakeholder confidence.
- Document data structures, transformations, business rules, and technical processes to support transparency, maintainability, and consistent use.
Business Intelligence & Data Accessibility
- Develop datasets and data structures that enable dashboards, visualization, reporting, and other stakeholder-facing analytical solutions.
- Support dashboard and visualization development using Power BI or comparable business intelligence platforms.
- Improve how business users and analytics teams access and use trusted data for recurring reporting and decision support.
Stakeholder Partnership & Continuous Improvement
- Partner with client stakeholders, analytics teams, business leaders, and technical partners to gather requirements and translate business needs into technical solutions.
- Communicate technical concepts, data limitations, dependencies, and delivery progress clearly to technical and nontechnical stakeholders.
- Identify and implement opportunities to automate data workflows, reduce manual processes, improve maintainability, and support geospatial or location-intelligence requirements where applicable.
Qualifications
Must-Have Requirements
- Approximately 3–4+ years of relevant experience in data engineering, analytics engineering, business intelligence, or a closely related field.
- Hands-on experience with Databricks or Microsoft Fabric, including practical experience developing data solutions rather than solely consuming platform outputs.
- Demonstrated experience building, maintaining, and troubleshooting ETL/ELT pipelines.
- Strong working knowledge of SQL, data transformation, data integration, and data modeling.
- Experience preparing structured datasets for business intelligence, dashboards, reporting, visualization, or stakeholder consumption.
- Understanding of data quality, validation, governance, and data-management practices.
- Demonstrated ability to translate business requirements into technical deliverables and collaborate effectively with business, client, and technical stakeholders.
Preferred Experience
- Experience working with both Databricks and Microsoft Fabric.
- Experience with Lakehouse architecture, Delta Lake, Unity Catalog, or comparable modern data-platform technologies.
- Experience using Python or another programming language for data engineering or automation.
- Experience developing or supporting solutions in Power BI, Tableau, or comparable visualization platforms.
- Experience with dimensional modeling, data warehousing, enterprise reporting, or enterprise data-management frameworks.
- Experience with Esri/ArcGIS, geospatial analytics, mapping, or location intelligence.
- Experience supporting enterprise clients, consulting engagements, client-facing analytics initiatives, or AI-enabled analytics technologies.
Technology & Tools
- Databricks and/or Microsoft Fabric
- SQL and ETL/ELT development technologies
- Data modeling, integration, and modern data-platform technologies
- Python
- Power BI or comparable business intelligence and visualization tools
- Delta Lake, Unity Catalog, or related Lakehouse technologies
- Esri/ArcGIS and geospatial analytics tools, where applicable
- AI-enabled analytics and automation solutions
Capabilities
- Technical problem-solving and structured analytical thinking.
- Ability to translate business requirements into scalable technical solutions.
- Strong attention to data accuracy, reliability, maintainability, and usability.
- Clear communication of technical concepts to business and client stakeholders.
- Organization and prioritization across concurrent technical requirements and projects.
- Cross-functional collaboration across business, analytics, and technical teams.
- Continuous improvement mindset focused on automation, scalability, data accessibility, and measurable business impact.
Education
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Data Analytics, or a related field preferred; equivalent relevant professional experience may be considered.
Cushman & Wakefield also provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health, vision, and dental insurance, flexible spending accounts, health savings accounts, retirement savings plans, life, and disability insurance programs, and paid and unpaid time away from work. In addition to a comprehensive benefits package, Cushman and Wakefield provide eligible employees with competitive pay, which may vary depending on eligibility factors such as geographic location, date of hire, total hours worked, job type, business line, and applicability of collective bargaining agreements.
The compensation that will be offered to the successful candidate will depend on factors such as whether the position is covered by a collective bargaining agreement, the geographic area in which the work will be performed, market pay rates in that area, and the candidate’s experience and qualifications.
The company will not pay less than minimum wage for this role.
The compensation for the position is: $106,250.00 - $125,000.00
Cushman & Wakefield is an Equal Opportunity employer to all protected groups, including protected veterans and individuals with disabilities. Discrimination of any type will not be tolerated.
In compliance with the Americans with Disabilities Act Amendments Act (ADAAA), if you have a disability and would like to request an accommodation in order to apply for a position at Cushman & Wakefield, please call the ADA line at 1-888-365-5406 or email Accommodations@cushwake.com. Please refer to the job title and job location when you contact us.
Data Analytics Engineer Job Roles in Missouri
See all 58+ Data Analytics Engineer Jobs in Missouri
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Search Data Analytics Engineer Jobs in MissouriData Analytics Engineer Jobs in Missouri: Frequently Asked Questions
Which companies sponsor visas for data analytics engineers in Missouri?
Edward Jones, Centene Corporation, Express Scripts, and Cerner (now Oracle Health) are among Missouri employers with documented H-1B sponsorship histories for data and engineering roles. Large logistics and insurance companies headquartered in the Kansas City and St. Louis metro areas also appear regularly in Department of Labor LCA filings for data analytics and data engineering positions.
Which visa types are most common for data analytics engineer roles in Missouri?
The H-1B is the most common visa for data analytics engineers in Missouri, as the role typically qualifies as a specialty occupation requiring a bachelor's degree or higher in computer science, statistics, or a related field. Candidates already holding L-1B intracompany transferee status or an O-1A for extraordinary ability may also find pathways, depending on their background and employer situation.
Which cities in Missouri have the most data analytics engineer sponsorship jobs?
St. Louis and Kansas City account for the large majority of data analytics engineer sponsorship opportunities in Missouri. St. Louis benefits from a concentration of financial services, healthcare IT, and insurance employers. Kansas City has a growing technology sector alongside established logistics and financial firms. Columbia sees some activity tied to the University of Missouri's research and healthcare systems.
How to find data analytics engineer visa sponsorship jobs in Missouri?
Migrate Mate filters job listings specifically for visa sponsorship eligibility, making it straightforward to search for data analytics engineer roles in Missouri without sorting through employers unlikely to sponsor. You can filter by state and role type to surface positions at Missouri-based companies with active sponsorship histories, which saves significant time compared to reviewing unfiltered postings.
Are there any Missouri-specific considerations for data analytics engineers seeking sponsorship?
Missouri's prevailing wage requirements for H-1B positions are set at the metropolitan level, so expected compensation differs between the St. Louis and Kansas City metro areas. University of Missouri and Washington University in St. Louis produce graduates who enter the local data engineering pipeline, which means competition for entry-level sponsored roles can be meaningful. Employers in healthcare and financial services tend to have more established sponsorship processes than early-stage companies.
What is the prevailing wage for sponsored data analytics engineer jobs in Missouri?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.