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Data Analytics Jobs in Michigan (NOW HIRING)

This role ensures that current data initiatives are intentionally designed to meet today's analytical needs while enabling future innovation through scalable, secure, and wellgoverned platforms. The ...

The Director, Data Analytics & Artificial Intelligence is a senior leadership role within DENSO North America's IT Digital Center (ITDC), responsible for defining the enterprise wide strategy for ...

Venteon is currently seeking a Senior Director of Data Analytics & AI to lead enterprise data strategy for a global manufacturing organization. This executive-level position will drive the ...

Engineering Data Analytics Specialist - Powertrain Programs Location: Hybrid, Dearborn Michigan Job Type: W2 Contract Expected Hours per Week: 40 Schedule: Monday-Friday, 8-5 Pay Range: $34-36 per ...

Design and implement analytics solutions that support decision-making and performance tracking * Analyze structured and unstructured data to uncover patterns, trends, and inconsistencies * Deliver ...

Develop and deliver standardized and ad hoc dashboards, reports, and performance analytics (budget-focused) * Analyze structured and unstructured data to extract insights for business decision-making

This pivotal role is ideal for candidates with a robust background in data analytics for engineering who are seeking to continue their career in the automotive industry. Responsibilities: * Safety ...

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Data Analytics information

See Michigan salary details

$21

$47

$82

How much do data analytics jobs pay per hour?

As of Jul 13, 2026, the average hourly pay for data analytics in Michigan is $47.72, according to ZipRecruiter salary data. Most workers in this role earn between $38.37 and $54.04 per hour, depending on experience, location, and employer.

How does a Data Analytics professional typically collaborate with other departments within an organization?

Data Analytics professionals frequently work alongside teams such as marketing, finance, operations, and product development to identify trends, solve business problems, and inform strategic decisions. Collaboration often involves gathering data requirements, interpreting findings, and presenting actionable insights in a clear and accessible manner. Effective communication and the ability to translate technical data into business terms are essential for ensuring recommendations are implemented and drive measurable impact. Regular cross-functional meetings and project-based teamwork are common, offering opportunities to learn from other disciplines and broaden one's organizational influence.

What is data analytics?

Data analytics is the process of examining raw data to uncover trends, patterns, and insights that can inform decision-making. Professionals in this field use statistical techniques, programming, and data visualization tools to interpret complex data sets. Data analytics is applied in various industries, including business, healthcare, finance, and technology, to optimize operations, improve customer experiences, and drive strategic initiatives. The field often requires knowledge of tools like Excel, SQL, Python, and specialized analytics platforms.

What is the difference between Data Analytics vs Data Analyst?

AspectData AnalyticsData Analyst
Role FocusAnalyzing large datasets to identify trends and insightsInterpreting data, creating reports, and supporting decision-making
Skills & CertificationsStatistical skills, data visualization, tools like SQL, Python, RData visualization, Excel, SQL, basic statistical knowledge
Work EnvironmentOften in data teams, tech companies, or consulting firmsBusiness units, marketing, finance, or operations teams
Common UsageRefers to the field or disciplineRefers to the job role or position

While both roles involve working with data, Data Analytics typically refers to the broader field or discipline focused on analyzing data to extract insights. A Data Analyst is a specific job role within that field, responsible for interpreting data, creating reports, and supporting business decisions.

What are the key skills and qualifications needed to thrive as a Data Analytics professional, and why are they important?

To thrive as a Data Analytics professional, you need strong quantitative analysis skills, proficiency in statistics, and a relevant degree such as in mathematics, computer science, or a related field. Experience with technical tools like SQL, Python or R, data visualization platforms (e.g., Tableau, Power BI), and sometimes certifications like Google Data Analytics or Microsoft Certified: Data Analyst Associate are highly valuable. Critical thinking, problem-solving, and effective communication are essential soft skills for interpreting data and presenting findings to stakeholders. These skills and qualities are crucial for transforming raw data into actionable insights that drive business decision-making.
What are the most commonly searched types of Data Analytics jobs in Michigan? The most popular types of Data Analytics jobs in Michigan are:
What cities in Michigan are hiring for Data Analytics jobs? Cities in Michigan with the most Data Analytics job openings:
Infographic showing various Data Analytics job openings in Michigan as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $99,251 per year, or $47.7 per hour.
Lead Data & Analytics Architect

Lead Data & Analytics Architect

Hylant

Grand Rapids, MI • On-site

Full-time

Re-posted 15 days ago


Hylant rating

9.8

Company rating: 9.8 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

2nd of 281 rated insurance


Job description

The Opportunity:

The Lead Data Architect exists to define, own, and evolve Hylant's enterprise application and information architecture. This role ensures that current data initiatives are intentionally designed to meet today's analytical needs while enabling future innovation through scalable, secure, and wellgoverned platforms. The position serves as a technical authority and strategic partner across data engineering, analytics, and business teams. This role will be measured by its contribution to business outcomes such as operational efficiency, adoption of self-service data products, and AI agent effectiveness.

In This Role You Will Execute On:

  • Define and drive the enterprise data architecture vision, ensuring alignment between business objectives, analytics needs, and platform capabilities (long term strategy and innovation roadmaps).

  • Responsible for application architecture (platform, tools, technologies) and information architecture (data models, data flow, data structures and data access)

  • Translate business and analytical requirements into scalable, secure, and feasible data architecture designs that support both nearterm delivery and longterm innovation.

  • Guide requirements gathering, backlog shaping, and solution design to ensure initiatives align with established architectural standards and futurestate roadmaps.

  • Lead the design of analytical data models, including dimensional and star schema designs for curated, businessready data layers.

  • Design and oversee endtoend data pipelines, including sourcetotarget mappings, transformation logic, and serving strategies.

  • Establish architectural patterns and standards for data ingestion, transformation, storage, governance, and analytics consumption.

  • Establish and enforce data governance frameworks, standards, and policies to ensure data quality, security, and compliance.

  • Ensure the integrity, quality, and validation of data across the full lifecycle, from source systems through curated datasets and reporting layers.

  • Partner closely with data engineering and analytics teams to provide architectural guidance throughout delivery while remaining accountable for solution quality. Mentor and guide the lead data engineer.

  • Own the Data Strategy & Lifecycle Management, treating EDW domains as data products with SLAs, ownership, and lifecycle

  • Contribute to AI, Machine Learning, and Analytics Enablement Roadmap.

  • Responsible for overseeing, integrating, and optimizing AI agents in data pipelines and ensuring the right mix of human and AI involvement. Ensure responsible use of AI agents and automation in data integration, transformation, and delivery.

  • Understand and own relationships with external support providers and vendors as needed.

  • Evaluate and recommend platform capabilities and emerging technologies to continuously improve performance, scalability, and usability of the data ecosystem. Ensure solutions and system are scalable, re-usable, and cost optimized.

  • Perform other duties and special projects as requested.

In This Role You'll Need:

  • Prefer bachelor's degree in computer science, data science, engineering, or a related field, or equivalent practical experience.

  • Insurance industry experience, including familiarity with data domains such as policy, claims, billing, underwriting, or risk.

  • Six or more years of experience in data architecture, analytics architecture, or enterprise data platform design.

  • Demonstrated experience designing and delivering data platforms built on Azure based technologies as well as with multi-cloud or hybrid environments.

  • Hands on experience with DevOps (CI/CD process), event streaming and processing, AI/ML toolset, Azure Databricks, Microsoft Data Factory, Delta Lake, Unity Catalog, and Azure cloud services.

  • Strong experience designing analytical data models, including dimensional and star schema approaches.

  • Advanced SQL skills and working proficiency with PySpark for data transformation and modeling.

  • Experience designing and validating end-to-end data pipelines, including data quality and reconciliation processes.

  • Ability to clearly communicate complex technical concepts to both technical and non-technical audiences.

  • Experience managing a team and in establishing an Architecture Review Board, Design Reviews, and Data Standards and Conventions.

  • Must be willing and able to travel for in-person meetings at least on a quarterly basis

  • Ability and willingness to travel by car or airplane for meetings, conferences, or other business-related functions.

  • Must be legally authorized to work in the United States


Why Hylant?

A multi-year recipient of Best Places to Work in Insurance, Hylant is a full-service insurance brokerage with over 20 offices in eight states. And since the founding of our family-owned business over 90 years ago, we made a promise to strengthen and protect the businesses, employees and communities of our client family by embracing them as our own. We're more than an insurance brokerage firm and you're more than a client, employee or neighbor. You're family. And that's just the way we treat you.

Hylant is proud to be an equal opportunity workplace. All qualified applicants will receive consideration for employment without regard to race, marital status, sex, age, color, religion, national origin, Veteran status, disability or any other characteristic protected by law. If you have a disability or special need that requires accommodation, please let us know. Hylant participates in E-Verify.


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