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Senior Metadata Analyst Jobs in Michigan (NOW HIRING)

K Anand Corporation

Senior Data Engineer

Detroit, MI · On-site

$97K - $131K/yr

You will collaborate across engineering, analytics, and business teams in an Agile delivery model ... Experience with data governance/metadata tools and practices (catalog, lineage, data quality ...

Mango Analytics

Data Architect with MDM

Auburn Hills, MI · On-site

$60.25 - $77.50/hr

This role will work under the direct leadership of the Senior Manager for Enterprise Data ... analyzing data and metadata. Experience with Enterprise Data Warehouse (EDW), Data Mart, and ...

Saanvi Technologies

Senior Data Product Manager

Dearborn, MI · On-site

$116K - $153K/yr

The ideal candidate will bridge business, engineering, analytics, and data science teams to deliver ... Drive data governance, metadata management, data quality, and compliance initiatives. * Develop ...

OneStream Software

Senior Product Manager I

Rochester, MI · On-site

$116K - $153K/yr

Description Senior Product Manager I Location: Remote, USA Employment Type: Full-Time Benefits ... metadata design, data integration, dashboards, graphs, and report authoring. * Ability to analyze ...

OneStream Software

Senior Product Manager I

Birmingham, MI · On-site

$120K - $159K/yr

Description Senior Product Manager I Location: Remote, USA Employment Type: Full-Time Benefits ... metadata design, data integration, dashboards, graphs, and report authoring. * Ability to analyze ...

Prophecy Technologies

Data Architect

Auburn Hills, MI · On-site

$60.25 - $77.50/hr

Data Architect (Senior Candidate) Location: Auburn Hills, MI 48326 3 days onsite Position ... analyzing data and metadata. Experience with Enterprise Data Warehouse (EDW), Data Mart, and ...

Deloitte

Clinical Data AMS Sr. Consultant

Midland, MI · On-site

Recruiting for this role ends on 10/1/2026 Position Summary The Clinical Data Analytics (CDA) AMS ... nodes, metadata server, workspace/stored process servers), ensuring high availability for ...

Deloitte

Clinical Data AMS Sr. Consultant

Lansing, MI · On-site

Recruiting for this role ends on 10/1/2026 Position Summary The Clinical Data Analytics (CDA) AMS ... nodes, metadata server, workspace/stored process servers), ensuring high availability for ...

Deloitte

Clinical Data AMS Sr. Consultant

Detroit, MI · On-site

Recruiting for this role ends on 10/1/2026 Position Summary The Clinical Data Analytics (CDA) AMS ... nodes, metadata server, workspace/stored process servers), ensuring high availability for ...

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All JobsMetadata Analyst JobsSenior Metadata Analyst JobsSenior Metadata Analyst Jobs in Michigan

Senior Metadata Analyst information

What does a senior metadata analyst do?

A Senior Metadata Analyst is responsible for managing and optimizing metadata, which is data that describes other data, within an organization's systems. They ensure the accuracy, consistency, and integrity of metadata to support data management, discovery, and governance initiatives. Senior Metadata Analysts often collaborate with IT, data governance, and business teams to create metadata standards and processes, and they may also use specialized tools to catalog and maintain metadata repositories.

What are the key skills and qualifications needed to thrive as a senior metadata analyst?

To thrive as a Senior Metadata Analyst, you need expertise in data management, metadata standards, and information architecture, often supported by a degree in information science or a related field. Familiarity with metadata management tools (such as Collibra or Informatica), data catalog systems, and data governance frameworks is typically required. Strong analytical thinking, attention to detail, and effective communication skills help in collaborating with stakeholders and ensuring data consistency. These skills are crucial for maintaining data quality, enabling efficient data discovery, and supporting organizational data governance initiatives.

How does a senior metadata analyst typically collaborate with other departments within an organization?

A Senior Metadata Analyst frequently works cross-functionally with teams such as data governance, IT, business intelligence, and compliance to ensure metadata standards and best practices are consistently applied. They often facilitate workshops, lead metadata documentation efforts, and provide guidance on data classification to support business needs. Effective collaboration is key, as they help bridge technical and business perspectives, ensuring data assets are discoverable, trustworthy, and aligned with organizational goals.

What are popular job titles related to Senior Metadata Analyst jobs in Michigan?

For Senior Metadata Analyst jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Senior Metadata Analyst jobs in Michigan look for?

The top searched job categories for Senior Metadata Analyst jobs in Michigan are:

What cities in Michigan are hiring for Senior Metadata Analyst jobs?

Cities in Michigan with the most Senior Metadata Analyst job openings:

Senior Metadata Analyst jobs near you
Infographic showing various Senior Metadata Analyst job openings in Michigan as of August 2026, with employment types broken down into 85% Full Time, 7% Part Time, 1% Temporary, and 7% Contract. Highlights an 81% Physical, 7% Hybrid, and 12% Remote job distribution.

Senior Data Engineer

Detroit, MI • On-site

K Anand Corporation
1 - 10 employees
Learn more about K Anand Corporationexternal

$97K - $131K/yr

Other

Posted 12 days ago

Job description

Job Title: Senior Data Engineer

Location: Detroit, MI (Onsite)

12 Months Contract

W2

Role Summary

We are looking for a Senior Data Engineer to design, build, and optimize scalable data pipelines and data platforms supporting analytics, reporting, and AI/ML use cases. The ideal candidate has strong hands-on experience with Snowflake on AWS, Python-based ETL/ELT development, and enterprise scheduling/orchestration tools like Control-M, along with legacy/enterprise ETL experience in IBM DataStage. You will collaborate across engineering, analytics, and business teams in an Agile delivery model.

Key Responsibilities

  • Design, develop, and maintain end-to-end data pipelines (batch and near real-time) using Snowflake, AWS services, and Python.
  • Build and optimize data models in Snowflake (e.g., dimensional modeling, data vault, or curated data marts) for analytics and downstream consumption.
  • Develop and maintain ETL/ELT workflows using Python and IBM DataStage; migrate/modernize workloads where applicable.
  • Implement job scheduling, monitoring, and operational support using Control-M (alerting, retries, SLAs, and dependency management).
  • Ensure data quality, governance, lineage, and documentation standards are met across pipelines.
  • Perform performance tuning and cost optimization across Snowflake and AWS (query optimization, clustering, warehouse sizing, storage management).
  • Partner with stakeholders (Data Science/AI, BI, Product, and Platform teams) to enable data products and AI-ready datasets.
  • Participate in Agile ceremonies, contribute to estimation, planning, and sprint execution; follow SDLC and change management processes.
  • Troubleshoot production issues, perform root-cause analysis, and drive preventative improvements.

Required Technical Skills

  • Snowflake: Strong expertise in Snowflake architecture, SQL development, performance tuning, security/roles, data loading/unloading, and best practices.
  • AWS: Hands-on experience with AWS data ecosystem (commonly S3, IAM, CloudWatch; plus services such as Glue, Lambda, EC2, Step Functions, EMR, or Kinesis as applicable).
  • Python: Strong Python programming for data engineering (ETL/ELT frameworks, API ingestion, automation, unit testing, logging).
  • Control-M: Experience designing and managing enterprise job scheduling, dependencies, calendars, SLAs, monitoring, and incident handling.
  • IBM DataStage: Solid experience building and maintaining DataStage jobs, handling complex transformations, and supporting production workloads.
  • SQL: Advanced SQL skills for transformations, optimization, and data validation across large datasets.
  • CI/CD & Version Control: Experience with Git and CI/CD practices for data pipelines (tools may vary).
  • Operational Excellence: Monitoring, alerting, and production support experience in a 24x7 or business-critical environment.

Good to Have

  • AI/ML exposure: Experience enabling AI/ML pipelines or feature datasets; familiarity with ML lifecycle concepts, feature engineering, or MLOps tools/processes.
  • Experience with data governance/metadata tools and practices (catalog, lineage, data quality frameworks).
  • Exposure to streaming or event-driven architectures.

Required Soft Skills

  • Strong experience working in Agile/Scrum teams and delivering within structured SDLC processes.
  • Excellent communication skills (technical and non-technical) with the ability to explain complex data concepts clearly.
  • Proven ability to coordinate across multiple teams (Data Engineering, Data Science, DevOps, Security, BI, and business stakeholders).
  • Strong ownership mindset, problem-solving ability, and attention to detail.

Qualifications (Typical)

  • Bachelor s degree in Computer Science, Engineering, or related field (or equivalent practical experience).
  • 9+ years of data engineering experience, including enterprise-grade data platform delivery and production support.

Thanks & Regards,

Aditya Kumar

Recruitment Manager Talent Acquisition

KAnand Corporation

Email:

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