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Remote Data Infrastructure Jobs in Michigan (NOW HIRING)

Utilidata

Principal Data Engineer

Ann Arbor, MI · On-site +1

$170K - $210K/yr

Translate complex data infrastructure decisions for non-technical stakeholders without oversimplifying, and break vague product requirements into clear engineering tasks and acceptance criteria

LHH US

Data Analyst

Zeeland, MI · Remote

$70K - $120K/yr

This is a unique opportunity to step into a role where you'll build and shape data infrastructure ... We will not consider remote candidates. Pay Details: $70,000.00 to $120,000.00 per year Search ...

Utilidata

AI Infrastructure Engineer

Ann Arbor, MI · On-site +1

$170K - $210K/yr

The AI Infrastructure Engineer is responsible for designing, building, and owning the end-to-end ... data science teams and is open to fully remote candidates, with periodic travel expected for ...

Utilidata

AI Infrastructure Engineer

Ann Arbor, MI · On-site +1

$170K - $210K/yr

The AI Infrastructure Engineer is responsible for designing, building, and owning the end-to-end ... data science teams and is open to fully remote candidates, with periodic travel expected for ...

Hitachi Careers

Global Solution Lead

MI · Remote

Remote role available to US based candidates. Our Company We're Hitachi Vantara, the data foundation trusted by the world's innovators. Our resilient, high-performance data infrastructure means that ...

Detroit Tigers

Cloud Data Engineer

Detroit, MI · On-site +1

$113.40K - $136.10K/yr

Build and maintain MLOps infrastructure to support the deployment, monitoring, and retraining of ... The location may be based in Detroit or fully remote. * Occasional evening, weekend, and holiday ...

NAVA Software Solutions

Cloud Architect - Remote

Lansing, MI · On-site +1

$66 - $84/hr

Cloud Infrastructure Architect Location: 100% Remote Duration: 12 months + Job Duties and ... Design and test large-scale workload and data migrations * Provide direct support to technical and ...

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What are the key skills and qualifications needed to thrive as a Remote Data Infrastructure Engineer, and why are they important?

To excel as a Remote Data Infrastructure Engineer, you need a strong background in computer science, data architecture, and experience with cloud platforms such as AWS, Azure, or Google Cloud. Familiarity with tools like Terraform, Kubernetes, and data pipeline technologies, as well as relevant certifications (e.g., AWS Certified Solutions Architect), is typically required. Strong problem-solving abilities, clear communication, and self-motivation are essential soft skills for remote collaboration and troubleshooting. These competencies ensure reliable, scalable data systems and effective teamwork across distributed environments.

What are some common challenges faced by professionals working in remote data infrastructure roles?

Professionals in remote data infrastructure roles often encounter challenges such as ensuring seamless communication across distributed teams, maintaining high availability and performance of data systems, and managing security risks associated with remote access. Coordinating with colleagues across different time zones can require flexibility in scheduling and proactive communication. Additionally, remote data infrastructure engineers must stay up-to-date with evolving cloud technologies and best practices to effectively support scalable, reliable, and secure data architectures.

What is remote data infrastructure?

Remote data infrastructure refers to the systems, tools, and processes that enable organizations to collect, store, manage, and analyze data from remote locations, often via cloud-based platforms. This infrastructure allows teams to access and work with data securely from anywhere, supporting distributed work environments and scalable data solutions. It typically involves cloud storage, data pipelines, databases, and security protocols tailored for remote accessibility. Remote data infrastructure is essential for businesses that operate in multiple locations or have remote teams.
What are the most commonly searched types of Data Infrastructure jobs in Michigan? The most popular types of Data Infrastructure jobs in Michigan are:
What are popular job titles related to Remote Data Infrastructure jobs in Michigan? For Remote Data Infrastructure jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Remote Data Infrastructure jobs in Michigan look for? The top searched job categories for Remote Data Infrastructure jobs in Michigan are:
What cities in Michigan are hiring for Remote Data Infrastructure jobs? Cities in Michigan with the most Remote Data Infrastructure job openings:
Remote Data Infrastructure jobs near you
Principal Data Engineer

Principal Data Engineer

Utilidata

Ann Arbor, MI • On-site, Remote

$170K - $210K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 17 days ago

Job description

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically orchestrate power and unlock more compute capacity from existing energy infrastructure. For over a decade, we have applied AI to the electric grid - bringing real-time visibility and power-flow control to complex energy infrastructure. Our Karman platform, built on a custom NVIDIA module, brings that same capability to AI data centers, giving operators a way to better use the power already available to them.
We're looking for a Principal Data Engineer to own the technical direction and execution of our data engineering platform. This role is responsible for setting architectural direction for the data systems that underpin our products, make critical design decisions about how we collect, process, store, and serve data at scale, and raise the bar for the entire team through your judgment, communication, and hands-on engineering. You'll operate at the intersection of deep technical work and cross-functional leadership, translating product goals into sound engineering plans and guiding the team through ambiguity to deliver real results. You'll own the component-level architecture for the data platform while working in close partnership with the platform architect to ensure alignment with the end-to-end platform vision and architecture. You'll join a diverse team of experts who are mission-driven, collaborative, and adaptive, and guide the team through the challenges of building reliable, performant data infrastructure in a fast-moving environment.
Responsibilities
  • Architect and contribute directly to core platform components, including ingestion pipelines, transformation frameworks, data models, and orchestration
  • Define and evolve the multi-quarter technical roadmap for the data platform, balancing new capabilities, reliability investments, and technical debt reduction in alignment with the broader platform architecture
  • Drive evaluation and adoption of tooling across the stack, ensuring choices are well-reasoned and aligned with where the platform needs to go
  • Lead architecture reviews and design discussions, ensuring decisions are well-reasoned, documented, and understood by the team
  • Cut through ambiguity by asking the right questions early about data quality, schema evolution, and downstream dependencies, and identify risks before they become crises
  • Translate complex data infrastructure decisions for non-technical stakeholders without oversimplifying, and break vague product requirements into clear engineering tasks and acceptance criteria
  • Partner closely with data science leads and cross-functional teams to surface dependencies and constraints early and prioritize improvements that unlock productivity
  • Run a lightweight but effective backlog and planning process, keeping the team focused and unblocked
  • Mentor and grow engineers with an emphasis on raising technical depth - delegate meaningful work, pair on hard problems, and create opportunities for others to stretch
  • Set code review standards, testing philosophy, and engineering best practices that make the whole team better, including data validation, pipeline testing, and schema management
  • Ensure data systems work reliably in production - instrumented, observable, and operable, with clear SLAs on freshness, completeness, and accuracy

Minimum Qualifications
  • At least 8 years of experience in data engineering, with 2+ years operating at a principal or staff level
  • Proven ability to design and evaluate end-to-end data platforms across ingestion, transformation, storage, and serving, with clean contracts between layers
  • Deep understanding of data pipeline design, with fluency in the patterns and tradeoffs of batch and streaming pipelines at scale
  • Strong understanding of data modeling and storage strategies
  • Strong software engineering fundamentals, with the depth to evaluate code quality and set architectural standards
  • Strong experience with cloud data infrastructure (AWS, GCP, or Azure) and the surrounding ecosystem
  • Demonstrated ability to lead technical teams, set direction, and grow engineers without relying on formal authority

Enhanced Qualifications (Nice to Have)
  • Experience with streaming architectures (Spark Structured Streaming, Delta Live Tables, Kafka)
  • Familiarity with data quality and observability tooling (Great Expectations, Monte Carlo, Soda, or similar)
  • Background working with visualization tools connected to Databricks (Databricks Dashboards, Tableau, Sigma, Power BI)
  • Experience with data collection from edge devices
  • Experience supporting ML workflows, including feature engineering pipelines, feature stores, or model input data preparation

Salary Range: $170,000 to $210,000 base compensation depending on experience plus stock options. Salary will be commensurate with an individual's skills, training, years of experience, and in line with internal compensation bands.
Location: This position can be performed remotely from anywhere in the United States.
Our Commitments
Utilidata values the diversity of our team. We provide equal employment opportunities without regard to race, color, religion, creed, sex, gender, sexual orientation, gender identity or expression, national origin, age, physical disability, mental disability, medical condition, pregnancy or childbirth, sexual orientation, genetics, genetic information, marital status, or status as a covered veteran or any other basis protected by applicable federal, state and local laws.
We are committed to:
  • Creating a diverse and inclusive workplace that is welcoming, supportive, affirming, and respectful
  • Empowering employees to solve problems and work together to make a difference
  • Providing mentorship and growth opportunities as part of a collaborative team
  • A flexible work environment with flexible paid time off
  • Competitive compensation and benefits, including health, dental, vision, and employer-match 401k

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