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Elt Developer Jobs in Michigan (NOW HIRING)

IntraEdge

AI Data Engineer

Detroit, MI

$113K - $136K/yr

... ELT) pipelines specifically for AI and ML models. * Architect data solutions: Develop and manage ... * DevOps and MLOps: Experience with CI/CD, Docker, and ML lifecycle management tools like MLflow ...

Tech Tammina LLC

Data / BI Architect

Pontiac, MI · On-site

... ETL/ELT: Cloud native (AWS Glue, Azure Data Factory, Google Cloud Dataflow) & in-warehouse transform tools (Fivetran, Talend, dbt); • Big Data Tech: Hadoop, Spark, Kafka; • Programming/API:

BDO USA

Power BI Lead Developer

Grand Rapids, MI · On-site

Strong ETL/ELT processes, required * Microsoft Power Automate Experience, preferred * Oracle ... Programming Interface, Data Analysis Expression, Power Automate, Python Individual salaries that ...

BDO

Power BI Lead Developer

Grand Rapids, MI · On-site

Strong ETL/ELT processes, required * Microsoft Power Automate Experience, preferred * Oracle ... Programming Interface, Data Analysis Expression, Power Automate, Python Individual salaries that ...

Ford Motor Company

Senior Data Engineer, CRM

Detroit, MI · On-site

$104K - $142K/yr

This role requires a hands-on engineer who excels at data modeling, ETL/ELT development, and the proactive management of data flows between Salesforce, MuleSoft, and our cloud environments. You'll ...

Programmers.io

Senior Databricks Architect

Detroit, MI · On-site

$64 - $84.25/hr

Lead the full Oracle → Databricks migration including schema translation, ETL/ELT logic ... Establish development best practices, coding standards, CI/CD, and DevOps/DataOps patterns.

DATAMAXIS

Analytics Engineer/Data Analyst

Okemos, MI · On-site

We are seeking an experienced Analytics Engineer to join our team on a contract basis. In this role ... Familiarity with ELT/ETL processes and data warehousing best practices. * Experience working with ...

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Elt Developer information

Will AI replace ETL developer?

AI is unlikely to fully replace ETL developers, as their role involves designing, maintaining, and troubleshooting complex data pipelines that require domain knowledge and problem-solving skills. Instead, AI tools can assist ETL developers by automating routine tasks and optimizing processes, allowing them to focus on more strategic aspects of data integration and architecture.

What are the key skills and qualifications needed to thrive as an ELT Developer, and why are they important?

To thrive as an ELT Developer, you need strong proficiency in database management, data warehousing concepts, and programming languages such as SQL and Python, often supported by a degree in computer science or a related field. Familiarity with ETL/ELT tools like Informatica, Talend, Apache NiFi, or cloud-based platforms such as AWS Glue and Azure Data Factory is typically required. Analytical thinking, problem-solving skills, and effective communication help you understand complex data requirements and collaborate with cross-functional teams. These skills and qualities are critical to ensure efficient, accurate data integration and transformation processes that support business intelligence and decision-making.

What do ETL developers do?

ETL developers design, build, and maintain processes that extract data from various sources, transform it into a suitable format, and load it into data warehouses or databases. They use tools like SQL, Python, or specialized ETL software to ensure data quality, accuracy, and efficiency for analytics and reporting. Strong problem-solving skills and knowledge of data modeling are essential for this role.

Are ETL developers in demand?

ETL developers are in high demand due to the increasing need for data integration and management in organizations. They often work with tools like SQL, Python, and data warehousing platforms, and their skills are valuable across industries that rely on large-scale data processing and analytics.

What are ELT Developers?

ELT Developers are professionals who specialize in designing, building, and maintaining data pipelines using the Extract, Load, Transform (ELT) process. They extract data from various sources, load it into a data warehouse or data lake, and then transform it within the storage system to support analytics and business intelligence. ELT Developers work with tools and platforms such as SQL, cloud data warehouses (like Snowflake or BigQuery), and ETL/ELT frameworks to ensure data is accurate, accessible, and well-structured for analysis.

How do ELT Developers typically collaborate with data analysts and engineers on projects?

ELT Developers often work closely with data analysts to understand data requirements and ensure the transformed data meets analytical needs. They also partner with data engineers to design and optimize pipelines for efficient data extraction, loading, and transformation. Regular meetings, code reviews, and shared documentation are common practices to facilitate smooth collaboration. Clear communication and teamwork are essential, as ELT Developers serve as a bridge between raw data sources and actionable business insights.

What is the difference between Elt Developer vs Data Engineer?

AspectElt DeveloperData Engineer
Required CredentialsBachelor's in CS or related field, knowledge of XML, XSLT, scriptingBachelor's in CS, experience with databases, programming, ETL tools
Work EnvironmentContent management, language localization, data transformation projectsData pipeline development, large-scale data processing, infrastructure setup
Employer & Industry UsageTech companies, localization firms, e-learning providersFinance, healthcare, tech firms managing big data

While both roles involve working with data, Elt Developers focus on language data transformation and localization tasks, whereas Data Engineers build and maintain data pipelines for large-scale data processing. The roles share some technical skills but differ in scope and industry focus.

What engineering jobs pay $500,000?

Senior software engineers, data engineers, and specialized engineering roles such as machine learning engineers or cloud architects can earn $500,000 or more annually, especially with experience, advanced skills, and in high-demand industries. These positions often require strong technical expertise, certifications, and sometimes leadership responsibilities or equity compensation.
What cities in Michigan are hiring for Elt Developer jobs? Cities in Michigan with the most Elt Developer job openings:
Elt Developer jobs near you
AI Data Engineer

AI Data Engineer

IntraEdge

Detroit, MI

$113K - $136K/yr

Full-time

Posted 6 days ago

Job description

Job Description: 

We are seeking an experienced and highly skilled AI Data Engineer to join our team. The successful candidate will be responsible for designing, building, and maintaining the data infrastructure and pipelines that power our AI, machine learning (ML), agentic AI, and generative AI (GenAI) initiatives. This role requires strong expertise in data engineering best practices and a deep understanding of the unique data needs of AI models. 
Key responsibilities
  • Build AI-ready data pipelines: Design, construct, and optimize scalable Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) pipelines specifically for AI and ML models.
  • Architect data solutions: Develop and manage data architectures, including data lakes, data warehouses, and vector databases, to support various AI workloads.
  • Ensure data quality and governance: Implement data validation, security, and governance policies to ensure the integrity, accessibility, and compliance of data used in AI models.
  • Support AI model lifecycle: Collaborate with data scientists and ML engineers to prepare, integrate, and manage large-scale datasets for model training and deployment.
  • Manage real-time data: Develop streaming data pipelines using technologies like Apache Kafka to support real-time AI applications and analytics.
  • Optimize cloud infrastructure: Utilize AWS cloud computing platforms to build, deploy, and scale AI data solutions efficiently.
  • Deploy AI models: Automate the training and deployment of AI/ML models into production via APIs and microservices.
  • Monitor and troubleshoot: Implement data observability tools to monitor pipeline health, identify data drift, and quickly resolve any data quality issues that may impact model performance.
  • AI-assisted development: Use AI assistants like Copilot in Microsoft Fabric notebooks to generate, explain, and fix code, accelerate data analysis, and streamline data transformation tasks.
Required qualifications
  • Education: A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field is typically required.
  • Experience: Proven experience in a data engineering or similar role, with specific experience supporting AI and ML projects.
  • Programming: Fluency in programming languages such as Python and SQL, and familiarity with others like Java or Scala.
  • Frameworks: Hands-on experience with ML frameworks like TensorFlow, PyTorch, and Scikit-learn, as well as LLM-specific tools like LangChain or LlamaIndex.
  • Big data: Experience with distributed data processing frameworks such as Apache Spark and Hadoop.
  • Cloud platforms: Proficiency with at least one major cloud provider (AWS, Azure, or GCP) and its AI data-related services.
  • Databases: Expertise in both relational (SQL) and NoSQL databases, including vector databases for GenAI applications.
  • DevOps and MLOps: Experience with CI/CD, Docker, and ML lifecycle management tools like MLflow is highly valued.

Job Description: 

We are seeking an experienced and highly skilled AI Data Engineer to join our team. The successful candidate will be responsible for designing, building, and maintaining the data infrastructure and pipelines that power our AI, machine learning (ML), agentic AI, and generative AI (GenAI) initiatives. This role requires strong expertise in data engineering best practices and a deep understanding of the unique data needs of AI models. 
Key responsibilities
  • Build AI-ready data pipelines: Design, construct, and optimize scalable Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) pipelines specifically for AI and ML models.
  • Architect data solutions: Develop and manage data architectures, including data lakes, data warehouses, and vector databases, to support various AI workloads.
  • Ensure data quality and governance: Implement data validation, security, and governance policies to ensure the integrity, accessibility, and compliance of data used in AI models.
  • Support AI model lifecycle: Collaborate with data scientists and ML engineers to prepare, integrate, and manage large-scale datasets for model training and deployment.
  • Manage real-time data: Develop streaming data pipelines using technologies like Apache Kafka to support real-time AI applications and analytics.
  • Optimize cloud infrastructure: Utilize AWS cloud computing platforms to build, deploy, and scale AI data solutions efficiently.
  • Deploy AI models: Automate the training and deployment of AI/ML models into production via APIs and microservices.
  • Monitor and troubleshoot: Implement data observability tools to monitor pipeline health, identify data drift, and quickly resolve any data quality issues that may impact model performance.
  • AI-assisted development: Use AI assistants like Copilot in Microsoft Fabric notebooks to generate, explain, and fix code, accelerate data analysis, and streamline data transformation tasks.
Required qualifications
  • Education: A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field is typically required.
  • Experience: Proven experience in a data engineering or similar role, with specific experience supporting AI and ML projects.
  • Programming: Fluency in programming languages such as Python and SQL, and familiarity with others like Java or Scala.
  • Frameworks: Hands-on experience with ML frameworks like TensorFlow, PyTorch, and Scikit-learn, as well as LLM-specific tools like LangChain or LlamaIndex.
  • Big data: Experience with distributed data processing frameworks such as Apache Spark and Hadoop.
  • Cloud platforms: Proficiency with at least one major cloud provider (AWS, Azure, or GCP) and its AI data-related services.
  • Databases: Expertise in both relational (SQL) and NoSQL databases, including vector databases for GenAI applications.
  • DevOps and MLOps: Experience with CI/CD, Docker, and ML lifecycle management tools like MLflow is highly valued. 
Education:Employment Type: FULL_TIME
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About IntraEdge

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At heart, we are a technology, products and services organization In our soul, it’s the people who make us what we are — the professionals we train and connect to next-level opportunities and the experts who create innovative solutions and value for our national and international partners. It’s true that innovative technology can provide a major boost to your business, but you also need the right talent pushing it forward. This critical combination is what we offer all of our partners: cutting edge tech solutions and the expertise to bring it to life.

Industry

It services

Company size

1,001 - 5,000 Employees

Headquarters location

Chandler, AZ, US

Year founded

2002

Social media

Instagram

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