Big Data Engineer Visa Sponsorship Jobs in Missouri
Big data engineer visa sponsorship jobs in Missouri are concentrated in St. Louis and Kansas City, where employers like Mastercard, Centene, and World Wide Technology run large data engineering teams. Missouri's financial services, healthcare IT, and logistics sectors generate steady demand for engineers with Hadoop, Spark, and distributed systems expertise, making it an active state for international candidates seeking sponsorship.
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Overview:
We're looking for a senior engineer who combines an architecture mindset with deep hands-on experience — someone who can design scalable systems and personally build and ship them into production. As our lead data engineer, you will own pipelines end-to-end across Google Cloud and Azure Databricks, from whiteboard to running code, while setting the technical direction for our enterprise data products, mentoring the team, and serving as the bridge between business stakeholders and engineering to turn strategic goals into robust, secure data solutions.
Responsibilities:
- Architect, build, and ship scalable batch and streaming data pipelines into production using BigQuery Dataform, Google Cloud Dataflow, Confluent Kafka, and Pub/Sub.
- Design and build data pipelines on Azure Databricks using Apache Spark, Delta Lake, and Unity Catalog, keeping engineering patterns consistent with our Google Cloud platform.
- Manage the end-to-end data product lifecycle, serving as the technical owner for critical data assets and establishing clear service level objectives.
- Provide technical leadership and mentorship to junior and senior engineers, conducting code reviews and fostering a culture of technical excellence.
- Lead the engineering team across Google Cloud and Azure Databricks environments, setting multi-cloud architecture standards for data movement, interoperability, security, and cost management.
- Partner with product managers, business analysts, and leadership to define data product requirements, align roadmaps, and manage engineering delivery schedules.
- Define, document, and enforce data engineering standards, including CI/CD practices, robust testing frameworks, and comprehensive technical documentation.
- Own the monitoring, cost optimization, and troubleshooting of production pipelines to maintain reliable business operations.
- Evaluate emerging technologies, particularly generative AI integrations and advanced governance tools, to continuously improve data platform capabilities.
Qualifications
Required:
- Bachelor Degree in Computer Science, Management Information Systems, Engineering or related field and 8 years Required
- Expert knowledge in programming languages and coding principles and procedures.
- Expert in web development framework.
- Strong attention to detail, facilitation, team building, collaboration, organization, and problem-solving skills.
- Excellent verbal and written communication skills.
- Ability to work methodically and analytically in a quantitative problem-solving environment.
- Demonstrated critical thinking skills.
- Expert in Microsoft Office Suite (Word, Excel, and PPT).
- Strong attention to detail, facilitation, team building and collaboration.
- Ability to obtain applicable certifications.
Strongly Preferred:
- Ten or more years of experience in data engineering, data warehousing, or data architecture, with at least five years in a technical leadership, mentoring, or consulting role.
- Deep technical expertise with Google Cloud, BigQuery, Dataflow, and related cloud data services.
- Hands-on production experience with Azure Databricks, including Apache Spark (PySpark), Delta Lake, and Unity Catalog.
- Proven experience architecting and leading delivery on multi-cloud data platforms, ideally spanning Google Cloud and Azure.
- Production experience designing and deploying real-time streaming architectures using messaging platforms like Confluent Kafka or Google Pub/Sub.
- Strong expertise in workflow orchestration using scheduling tools like Airflow.
- Advanced SQL skills and extensive experience with transformation frameworks like Dataform or dbt.
- Production experience with at least one transactional database, such as Oracle, SQL Server, or PostgreSQL.
- Strong hands-on coding skills in Python or Java, with a track record of personally shipping production-grade data pipelines.
- Demonstrated experience managing data product delivery, defining schemas, and establishing data quality baselines.
- Strong communication skills with a proven track record of collaborating with cross-functional stakeholders and translating business needs into technical specifications.
- Strong problem-solving abilities and experience leading engineering teams in fast-paced environments.
- Experience coding with agentic tooling as part of generative AI workflows.
- Direct experience implementing data mesh principles, managing data products, and using tools like Knowledge Catalog (Dataplex) or Entropy Data for contract management.
- Advanced knowledge of data security, compliance, and governance tooling such as Immuta and native BigQuery security controls.
- Experience operating across hybrid or multi-data platform environments, including Palantir.
- Google Cloud Professional Data Engineer or Professional Cloud Architect certification.
- Databricks Certified Data Engineer Professional or Microsoft Azure data certifications, plus certifications in supporting technologies such as Power BI.
This job posting will remain open a minimum of 72 hours and on an ongoing basis until filled.
EEO/Disabled/Veterans
Job Web Development
Primary Location US-MO-Kansas City
Schedule: Full-time
Travel: No
Req ID: 265156
Job Hire Type Experienced #LI-MJ #COR
Description
Overview:
We're looking for a senior engineer who combines an architecture mindset with deep hands-on experience — someone who can design scalable systems and personally build and ship them into production. As our lead data engineer, you will own pipelines end-to-end across Google Cloud and Azure Databricks, from whiteboard to running code, while setting the technical direction for our enterprise data products, mentoring the team, and serving as the bridge between business stakeholders and engineering to turn strategic goals into robust, secure data solutions.
Responsibilities:
- Architect, build, and ship scalable batch and streaming data pipelines into production using BigQuery Dataform, Google Cloud Dataflow, Confluent Kafka, and Pub/Sub.
- Design and build data pipelines on Azure Databricks using Apache Spark, Delta Lake, and Unity Catalog, keeping engineering patterns consistent with our Google Cloud platform.
- Manage the end-to-end data product lifecycle, serving as the technical owner for critical data assets and establishing clear service level objectives.
- Provide technical leadership and mentorship to junior and senior engineers, conducting code reviews and fostering a culture of technical excellence.
- Lead the engineering team across Google Cloud and Azure Databricks environments, setting multi-cloud architecture standards for data movement, interoperability, security, and cost management.
- Partner with product managers, business analysts, and leadership to define data product requirements, align roadmaps, and manage engineering delivery schedules.
- Define, document, and enforce data engineering standards, including CI/CD practices, robust testing frameworks, and comprehensive technical documentation.
- Own the monitoring, cost optimization, and troubleshooting of production pipelines to maintain reliable business operations.
- Evaluate emerging technologies, particularly generative AI integrations and advanced governance tools, to continuously improve data platform capabilities.
Qualifications
Required:
- Bachelor Degree in Computer Science, Management Information Systems, Engineering or related field and 8 years Required
- Expert knowledge in programming languages and coding principles and procedures.
- Expert in web development framework.
- Strong attention to detail, facilitation, team building, collaboration, organization, and problem-solving skills.
- Excellent verbal and written communication skills.
- Ability to work methodically and analytically in a quantitative problem-solving environment.
- Demonstrated critical thinking skills.
- Expert in Microsoft Office Suite (Word, Excel, and PPT).
- Strong attention to detail, facilitation, team building and collaboration.
- Ability to obtain applicable certifications.
Strongly Preferred:
- Ten or more years of experience in data engineering, data warehousing, or data architecture, with at least five years in a technical leadership, mentoring, or consulting role.
- Deep technical expertise with Google Cloud, BigQuery, Dataflow, and related cloud data services.
- Hands-on production experience with Azure Databricks, including Apache Spark (PySpark), Delta Lake, and Unity Catalog.
- Proven experience architecting and leading delivery on multi-cloud data platforms, ideally spanning Google Cloud and Azure.
- Production experience designing and deploying real-time streaming architectures using messaging platforms like Confluent Kafka or Google Pub/Sub.
- Strong expertise in workflow orchestration using scheduling tools like Airflow.
- Advanced SQL skills and extensive experience with transformation frameworks like Dataform or dbt.
- Production experience with at least one transactional database, such as Oracle, SQL Server, or PostgreSQL.
- Strong hands-on coding skills in Python or Java, with a track record of personally shipping production-grade data pipelines.
- Demonstrated experience managing data product delivery, defining schemas, and establishing data quality baselines.
- Strong communication skills with a proven track record of collaborating with cross-functional stakeholders and translating business needs into technical specifications.
- Strong problem-solving abilities and experience leading engineering teams in fast-paced environments.
- Experience coding with agentic tooling as part of generative AI workflows.
- Direct experience implementing data mesh principles, managing data products, and using tools like Knowledge Catalog (Dataplex) or Entropy Data for contract management.
- Advanced knowledge of data security, compliance, and governance tooling such as Immuta and native BigQuery security controls.
- Experience operating across hybrid or multi-data platform environments, including Palantir.
- Google Cloud Professional Data Engineer or Professional Cloud Architect certification.
- Databricks Certified Data Engineer Professional or Microsoft Azure data certifications, plus certifications in supporting technologies such as Power BI.
This job posting will remain open a minimum of 72 hours and on an ongoing basis until filled.
EEO/Disabled/Veterans
Job Web Development
Primary Location US-MO-Kansas City
Schedule: Full-time
Travel: No
Req ID: 265156
Job Hire Type Experienced #LI-MJ #COR
Big Data Engineer Job Roles in Missouri
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Search Big Data Engineer Jobs in MissouriBig Data Engineer Jobs in Missouri: Frequently Asked Questions
Which companies sponsor visas for big data engineers in Missouri?
Mastercard's St. Louis operations, Centene Corporation, World Wide Technology, and Edward Jones have filed Labor Condition Applications for data engineering roles in Missouri. Large healthcare systems like SSM Health and BJC HealthCare also sponsor data engineers as they expand analytics infrastructure. Financial technology firms in Kansas City, including Cerner (now Oracle Health), have historically been active sponsors for distributed systems and pipeline engineering roles.
Which visa types realistically fit big data engineer roles in Missouri?
Big data engineer roles qualify as specialty occupations requiring at least a bachelor's degree in computer science, information systems, or a related field, making H-1B visa the primary visa pathway. Canadian and Mexican nationals with an engineering or computer science degree may qualify under the TN visa as a Computer Systems Analyst or Engineer. Singaporean nationals can use the H-1B1 visa and Australian nationals the E-3 visa, both of which cover specialty occupation roles. F-1 students may work via OPT or, with a qualifying STEM-designated degree, the 24-month STEM OPT extension.
Which cities in Missouri have the most big data engineer sponsorship jobs?
St. Louis generates the highest concentration of sponsored big data engineering positions in Missouri, driven by its financial services, healthcare IT, and technology consulting sectors. Kansas City follows closely, with strong demand from healthcare data firms and logistics technology companies. Smaller pockets of activity exist near Columbia, home to the University of Missouri's research computing programs, though the volume of corporate sponsorship there is significantly lower than in the two major metros.
How to find big data engineer visa sponsorship jobs in Missouri?
Migrate Mate lists Missouri employers with verified sponsorship history for big data engineer roles, so you can focus your search on companies that have already filed for similar positions rather than applying broadly. Filtering by Missouri and your specific technical stack, such as Spark, Kafka, or cloud data platforms, helps surface the most relevant openings. Migrate Mate's data reflects actual Labor Condition Application filing activity, giving you a clearer picture of which Missouri employers actively sponsor this role.
Are there state-specific factors that affect big data engineer sponsorship in Missouri?
Missouri's lower cost of operations compared to coastal tech hubs attracts mid-sized financial services and healthcare IT firms that run substantial data engineering teams with realistic sponsorship budgets. The presence of major anchor employers like Mastercard and Centene creates secondary demand among their vendors and technology partners. Missouri does not have state-level visa or work authorization programs, so sponsorship depends entirely on individual employer decisions and federal visa category eligibility.
What is the prevailing wage for sponsored big data 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.