Lead Infrastructure Engineer Visa Sponsorship Jobs in Michigan
Lead infrastructure engineer jobs in Michigan draw from the state's expanding tech sector, with employers like Ford Motor Company, General Motors, Stellantis, and Rocket Companies in Detroit and Ann Arbor actively building out cloud and systems infrastructure teams. Michigan's automotive and financial services industries rely on senior infrastructure talent, creating consistent demand for visa sponsorship roles across the state.
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Get Access To All JobsINTRODUCTION
The Senior Data Engineer – Platform Foundation is a hands-on, senior-level contributor embedded in the Foundations squad. You will design, build, and evolve the shared ingestion platform that underpins data delivery across the company. The platform is the product — your job is to make it reliable, extensible, and easy for other teams to adopt.
The Foundations squad operates across three pillars: simplifying the overall data platform landscape by reducing complexity and consolidating redundant patterns; enabling structured and unstructured data ingestion at scale; and supporting the exposure of data products to consumers across the organization. You contribute to all three — making architectural decisions, writing production code, and enabling other teams through documentation and hands-on support.
ROLE AND RESPONSIBILITIES
Platform Foundation Development
- Design and implement reusable ingestion components using dlt and dbt-core, covering both structured and unstructured data sources, handling high-volume, append-heavy, and schema-drifting patterns
- Own the Airflow platform end-to-end: extend and maintain DAGs and shared operators, handle deployments and version upgrades, and provide hands-on support to consuming teams
- Ensure incremental loading strategies, data quality checks, and lineage metadata are first-class outputs of every pipeline
Platform Simplification & Architecture
- Identify and eliminate redundant ingestion patterns across consuming teams, drive standardization onto shared Platform Foundation components
- Collaborate with Solution Architects to evolve the platform architecture in response to new data sources and shifting business requirements
- Support data product exposure: define and implement governed interfaces that make data reliably accessible to internal consumers
- Contribute to Terraform-managed infrastructure; participate in multi-cloud (AWS / Azure) deployment patterns
AI Tooling & Developer Productivity
- Actively use and evaluate AI-assisted development tools (GitHub Copilot, Claude Code, etc.) to accelerate platform Foundation delivery
- Champion AI tooling adoption within the squad; share best practices and guardrails around AI-generated code review
- Explore AI-powered capabilities (RAG pipelines, LLM-assisted data cataloguing) for internal platform documentation and self-service enablement
DevOps & Reliability
- Maintain and improve CI/CD pipelines (TeamCity, GitHub Actions) for platform Foundation components
- Define and enforce observability standards: DAG/Task-level alerting, SLA tracking
- Participate in on-call rotation for critical ingestion pipelines; drive post-incident improvements
Team Enablement & Stakeholder Management
- Produce platform Foundation documentation, runbooks, and enablement materials for consuming squads
- Translate ambiguous or moving business requirements into concrete technical designs — comfortable challenging scope when needed
- Mentor mid-level engineers; participate in hiring and technical assessments
BASIC QUALIFICATIONS
- Bachelor's degree in Business, Information Systems, Data/Analytics, Computer Science, or related field
- Minimum 5 years in data engineering roles, with at least 2 years in a senior / platform-level position
- Proven track record building production ingestion and transformation pipelines at scale
- Experience contributing to a shared platform or internal developer tooling consumed by multiple teams
CORE TECHNICAL SKILLS
- Python: idiomatic, testable, production-grade code — not just scripting
- dbt-core: advanced modelling (custom materializations), testing, documentation, packages
- Apache Airflow: DAG design patterns, custom operators, dynamic task mapping, SLA management
- Cloud data platforms: comfortable with one or more major cloud warehouses (Snowflake, BigQuery, Databricks, Microsoft Fabric)
- SQL: complex analytical queries, window functions, query profiling
- Git, CI/CD: trunk-based development, automated testing gates, pipeline-as-code
AI & MODERN TOOLING
- Daily user of AI coding assistants (Copilot, Claude Code or equivalent)
- Understands the limits of AI-generated code — applies rigorous review, not blind trust
- Interest in LLM-powered data tooling (RAG pipelines, Cortex, semantic layers) is a plus
INTRODUCTION
The Senior Data Engineer – Platform Foundation is a hands-on, senior-level contributor embedded in the Foundations squad. You will design, build, and evolve the shared ingestion platform that underpins data delivery across the company. The platform is the product — your job is to make it reliable, extensible, and easy for other teams to adopt.
The Foundations squad operates across three pillars: simplifying the overall data platform landscape by reducing complexity and consolidating redundant patterns; enabling structured and unstructured data ingestion at scale; and supporting the exposure of data products to consumers across the organization. You contribute to all three — making architectural decisions, writing production code, and enabling other teams through documentation and hands-on support.
ROLE AND RESPONSIBILITIES
Platform Foundation Development
- Design and implement reusable ingestion components using dlt and dbt-core, covering both structured and unstructured data sources, handling high-volume, append-heavy, and schema-drifting patterns
- Own the Airflow platform end-to-end: extend and maintain DAGs and shared operators, handle deployments and version upgrades, and provide hands-on support to consuming teams
- Ensure incremental loading strategies, data quality checks, and lineage metadata are first-class outputs of every pipeline
Platform Simplification & Architecture
- Identify and eliminate redundant ingestion patterns across consuming teams, drive standardization onto shared Platform Foundation components
- Collaborate with Solution Architects to evolve the platform architecture in response to new data sources and shifting business requirements
- Support data product exposure: define and implement governed interfaces that make data reliably accessible to internal consumers
- Contribute to Terraform-managed infrastructure; participate in multi-cloud (AWS / Azure) deployment patterns
AI Tooling & Developer Productivity
- Actively use and evaluate AI-assisted development tools (GitHub Copilot, Claude Code, etc.) to accelerate platform Foundation delivery
- Champion AI tooling adoption within the squad; share best practices and guardrails around AI-generated code review
- Explore AI-powered capabilities (RAG pipelines, LLM-assisted data cataloguing) for internal platform documentation and self-service enablement
DevOps & Reliability
- Maintain and improve CI/CD pipelines (TeamCity, GitHub Actions) for platform Foundation components
- Define and enforce observability standards: DAG/Task-level alerting, SLA tracking
- Participate in on-call rotation for critical ingestion pipelines; drive post-incident improvements
Team Enablement & Stakeholder Management
- Produce platform Foundation documentation, runbooks, and enablement materials for consuming squads
- Translate ambiguous or moving business requirements into concrete technical designs — comfortable challenging scope when needed
- Mentor mid-level engineers; participate in hiring and technical assessments
BASIC QUALIFICATIONS
- Bachelor's degree in Business, Information Systems, Data/Analytics, Computer Science, or related field
- Minimum 5 years in data engineering roles, with at least 2 years in a senior / platform-level position
- Proven track record building production ingestion and transformation pipelines at scale
- Experience contributing to a shared platform or internal developer tooling consumed by multiple teams
CORE TECHNICAL SKILLS
- Python: idiomatic, testable, production-grade code — not just scripting
- dbt-core: advanced modelling (custom materializations), testing, documentation, packages
- Apache Airflow: DAG design patterns, custom operators, dynamic task mapping, SLA management
- Cloud data platforms: comfortable with one or more major cloud warehouses (Snowflake, BigQuery, Databricks, Microsoft Fabric)
- SQL: complex analytical queries, window functions, query profiling
- Git, CI/CD: trunk-based development, automated testing gates, pipeline-as-code
AI & MODERN TOOLING
- Daily user of AI coding assistants (Copilot, Claude Code or equivalent)
- Understands the limits of AI-generated code — applies rigorous review, not blind trust
- Interest in LLM-powered data tooling (RAG pipelines, Cortex, semantic layers) is a plus
Lead Infrastructure Engineer Job Roles in Michigan
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Search Lead Infrastructure Engineer Jobs in MichiganLead Infrastructure Engineer Jobs in Michigan: Frequently Asked Questions
Which companies sponsor visas for lead infrastructure engineers in Michigan?
Michigan's largest visa sponsors for infrastructure engineering roles are concentrated in automotive technology and enterprise IT. Ford Motor Company, General Motors, Stellantis, and Rocket Companies have all filed Labor Condition Applications for senior infrastructure positions in the Detroit metro area. Healthcare systems like Henry Ford Health and Beaumont Health, along with university-affiliated research organizations in Ann Arbor, also sponsor infrastructure engineers with demonstrated leadership experience.
Which visa types realistically apply to lead infrastructure engineer roles in Michigan?
Lead infrastructure engineer roles qualify as specialty occupations requiring a bachelor's degree in computer science, information systems, or a directly related engineering field. H-1B visa is the primary path, subject to the annual cap and selection process. Canadian and Mexican nationals with an engineering degree may qualify under TN visa status. Singaporean and Chilean nationals can explore H-1B1 visa. Candidates already in H-1B visa status can transfer to a new Michigan employer once the new petition is filed.
Which cities in Michigan have the most lead infrastructure engineer sponsorship jobs?
Detroit and its surrounding suburbs, particularly Dearborn, Auburn Hills, and Troy, concentrate the highest volume of lead infrastructure engineer sponsorship opportunities, driven by automotive OEMs and their technology divisions. Ann Arbor is a secondary hub with strong employer presence from the University of Michigan, medical research institutions, and cloud-focused startups. Grand Rapids has a growing healthcare IT sector that also sponsors infrastructure engineering talent.
How to find lead infrastructure engineer visa sponsorship jobs in Michigan?
Migrate Mate lists Michigan employers with verified visa sponsorship history for lead infrastructure engineer roles, so you can focus your search on companies that have already filed for this type of position. The platform shows sponsorship activity specific to infrastructure and IT roles, helping you identify active sponsors in Detroit, Ann Arbor, and Grand Rapids without sorting through employers who do not sponsor.
Are there state-specific factors that affect visa sponsorship for lead infrastructure engineers in Michigan?
Michigan's infrastructure engineering market is shaped heavily by the automotive industry's digital transformation, which has pushed OEMs and their Tier 1 suppliers to hire senior infrastructure talent for cloud migration and DevOps initiatives. Many Michigan employers in this space have established immigration programs and prior LCA filing history. University of Michigan and Michigan State also serve as pipelines for OPT and STEM OPT candidates entering infrastructure roles in the state.
What is the prevailing wage for sponsored lead infrastructure engineer jobs in Michigan?
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.