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Data Modernization Jobs in Michigan (NOW HIRING)

This role supports both on-premises and cloud environments, contributes to enterprise data modernization efforts, and plays a key role in migrating DataStage workloads to IBM Cloud Pak for Data (CP4D)

Senior Databricks Architect

Detroit, MI ยท On-site

$64 - $84.25/hr

Collaborate with business and technical stakeholders to drive data modernization strategy. * Establish development best practices, coding standards, CI/CD, and DevOps/DataOps patterns. * Provide ...

Data Modernization: Leading the migration and integration path from legacy on-premise systems (including legacy Hadoop clusters) to modern, cloud-native data platforms on GCP. * Domain Expertise:

... data modernization, automation, and system optimization initiatives Partner closely with business and executive leaders to ensure technology solutions support operational requirements Manage capital ...

AI/ML and Data Engineer

Southfield, MI ยท On-site +1

$104K - $125K/yr

Provide executive-level advisory services on AI adoption and data modernization, tailoring recommendations for both technical and non-technical stakeholders and enabling informed decision-making.

AI/ML and Data Engineer

Southfield, MI

$104K - $125K/yr

Provide executive-level advisory services on AI adoption and data modernization, tailoring recommendations for both technical and non-technical stakeholders and enabling informed decision-making.

Data Engineer

Lansing, MI ยท On-site

$116K - $139K/yr

Support modernization efforts of the disease surveillance system, ensuring automated processes function correctly, data integrity, and SEM/SUITE compliance. * Provide technical leadership and ...

Supporting the design and modernization of cyber data and analytics programs that improve organizational intelligence and enable scalable delivery models * Developing and applying analytics, machine ...

Support the migration of onpremise DataStage jobs to IBM Cloud Pak for Data (CP4D), including code refactoring, testing, validation, and workflow modernization. Use Python and XML to automate ...

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Data Modernization information

What is the difference between Data Modernization vs Data Analyst?

AspectData ModernizationData Analyst
Primary FocusUpgrading and transforming data systems and infrastructureAnalyzing data to generate insights and reports
Skills RequiredData architecture, cloud platforms, database managementStatistical analysis, data visualization, SQL
Work EnvironmentIT departments, data engineering teamsBusiness units, analytics teams
CertificationsCloud certifications, data management certificationsData analysis, visualization certifications

Data Modernization involves upgrading data systems and infrastructure to improve efficiency and scalability, often requiring technical expertise in data architecture and cloud platforms. In contrast, Data Analysts focus on interpreting data, creating reports, and providing insights to support business decisions. While both roles work with data, their core responsibilities and skill sets differ significantly.

What are some common challenges faced by professionals working in data modernization projects?

Professionals in Data Modernization often encounter challenges such as integrating legacy systems with modern cloud-based solutions, ensuring data quality during migration, and managing data security and compliance. Additionally, they may need to collaborate closely with cross-functional teams to align business goals with technical requirements. Adaptability and strong communication skills are important, as priorities can shift rapidly in response to evolving business needs and technology updates.

What are the key skills and qualifications needed to thrive in data modernization?

To thrive in Data Modernization, you need strong expertise in data architecture, cloud platforms, and data migration, often supported by a degree in computer science or information systems. Familiarity with tools like Azure, AWS, Snowflake, ETL frameworks, and certifications such as AWS Certified Data Analytics or Microsoft Azure Data Engineer are commonly required. Excellent problem-solving, project management, and communication skills help professionals effectively lead transformation initiatives and collaborate with stakeholders. These skills are crucial for ensuring seamless migration, maximizing data value, and driving innovation within organizations.
Infographic showing various Data Modernization job openings in Michigan as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Data Warehouse Architect 3

HireITPeople

Lansing, MI โ€ข On-site

Contractor

Posted 27 days ago


Job description

The ETL Developer is responsible for designing, developing, and maintaining high-quality data integration solutions using IBM DataStage and related technologies.

This role supports both on-premises and cloud environments, contributes to enterprise data modernization efforts, and plays a key role in migrating DataStage workloads to IBM Cloud Pak for Data (CP4D). The developer will collaborate with technical and business teams to deliver reliable, scalable, and secure data pipelines aligned with organizational objectives.

Responsibilities and Technical Skills:

• Develop, enhance, and optimize ETL pipelines using IBM DataStage, including parallel and server jobs, job sequencing, and performance tuning.

• Support the migration of on-premises DataStage jobs to IBM Cloud Pak for Data (CP4D), including code refactoring, testing, validation, and workflow

modernization.

• Use Python and XML to automate processes, perform data transformations, and integrate automation into ETL workflows.

• Work extensively in Linux/Unix environments to write shell scripts, manage file systems, monitor processes, and troubleshoot runtime issues.

• Apply Master Data Management (MDM) principles to ensure data quality, governance, and consistency across enterprise systems.

• Develop complex SQL queries for data extraction, transformation, validation, and performance improvement across relational database platforms.

• Work within Agile teams to support sprint activities, deployments, documentation, and continuous improvement practices.

• Collaborate with data architects, analysts, DBAs, and business users to ensure successful and accurate delivery of data solutions.

• Troubleshoot ETL issues, perform root-cause analysis, recommend improvements, and ensure adherence to data standards and security policies.

Top Skills & Years of Experience:

- 5+ years of experience with ETL (IBM DataStage) - Required

- 1+ years of exposure to Cloud Pak for data - Required

- 5+ years of experience with Unix/Linux

- 3+ years of experience with Master Data Management

Desired Skills:

- Previous Government experience.