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Data Bi Engineer Jobs in Michigan (NOW HIRING)

Tech Tammina LLC

Data / BI Architect

Pontiac, MI · On-site

Data Business Intelligence (BI) Architect role is a hybrid of data architecture, engineering & business strategy, bridging the gap between tech data solutions & business objectives. Designs, develops ...

Tech Tammina LLC

Data / BI Architect

Pontiac, MI · On-site

$63.25 - $81.50/hr

... Programming for data visualizations, Python, TensorFlow, PyTorch, Keras, Scikit-learn, Apache Spark, Databricks, Jupyter Notebooks, AWS (SageMaker, EC2, S3), Azure (Machine Learning Studio ...

Thecsp

BI Data Engineer

Auburn Hills, MI

$108.40K - $130.10K/yr

Help translate business requirements (provided by the BI Business Analyst) into clean, well-organized data structures, with guidance from senior engineers. * Write SQL queries and basic Python ...

CGI Inc.

Senior Power BI Developer

Lansing, MI · On-site

Senior Power BI Developer Category: Software Development/ Engineering Main location: United States ... CGI is seeking a PowerBI Developer / SME to perform data analysis and modeling, develop dashboards ...

Guru Schools

Junior Power BI Developer

Detroit, MI · On-site

$66.30K - $86.10K/yr

Remote (Work From Home) Employment Type: Full-Time Job Summary We are looking for a detail-oriented Junior Power BI Developer to support our data analytics and reporting functions. This role is well ...

BDO USA

Power BI Lead Developer

Grand Rapids, MI · On-site

The Power BI Lead Developer is a role withing the Finance department where hands on experience ... Explores large data sets and relational databases, perform analyses and identify unique ...

BDO

Power BI Lead Developer

Grand Rapids, MI

The Power BI Lead Developer is a role withing the Finance department where hands on experience ... Explores large data sets and relational databases, perform analyses and identify unique ...

Atwell, LLC

Enterprise Data Engineer

Southfield, MI

$92K - $120K/yr

Integrate data from ERP and other business systems to support analytics and reporting initiatives ... Collaborate with BI developers and analysts to support Power BI datasets and reporting solutions.

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Data Bi Engineer information

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

To thrive as a Data BI Engineer, you need strong skills in data modeling, SQL, ETL processes, and a background in computer science or a related field. Familiarity with BI tools such as Power BI, Tableau, or Looker, as well as experience with data warehouses and cloud platforms like AWS or Azure, is typically required. Critical thinking, problem-solving, and effective communication are crucial soft skills for translating data insights into actionable business recommendations. These skills and qualities are essential for building reliable data solutions that empower organizations to make informed, data-driven decisions.

How does a Data BI Engineer typically collaborate with business stakeholders and data analysts?

A Data BI Engineer frequently works with business stakeholders and data analysts to understand data requirements, translate business needs into technical specifications, and ensure data solutions align with organizational goals. This role often involves participating in meetings to gather requirements, sharing progress updates, and iterating on dashboards or data pipelines based on feedback. Effective communication is key, as Data BI Engineers must bridge the gap between technical data structures and actionable business insights. Regular collaboration helps ensure that the data solutions provided are both technically sound and valuable for decision-making.

What are Data BI Engineers?

Data BI (Business Intelligence) Engineers are professionals who design, build, and maintain systems that transform raw data into meaningful business insights. They develop data pipelines, integrate various data sources, and create reports or dashboards to support decision-making processes. Their work ensures that companies have accurate, timely, and actionable information to drive strategy and operations. Data BI Engineers typically work closely with data analysts, data scientists, and business stakeholders.

What is the difference between Data Bi Engineer vs Data Analyst?

AspectData Bi EngineerData Analyst
Primary FocusBuilding data pipelines, data warehousing, and integrating data systemsAnalyzing data to generate reports and insights
Skills & ToolsSQL, ETL processes, data modeling, cloud platformsExcel, SQL, visualization tools like Tableau or Power BI
Work EnvironmentData engineering teams, IT departments, cloud environmentsBusiness units, analytics teams, management
CredentialsData engineering certifications, SQL, cloud certificationsData analysis certifications, SQL, visualization skills

While both roles work with data, Data Bi Engineers focus on building and maintaining data infrastructure, whereas Data Analysts interpret data to provide actionable insights. Understanding these differences helps organizations assign the right responsibilities and professionals for their data needs.

What are popular job titles related to Data Bi Engineer jobs in Michigan? For Data Bi Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Data Bi Engineer jobs in Michigan look for? The top searched job categories for Data Bi Engineer jobs in Michigan are:
What cities in Michigan are hiring for Data Bi Engineer jobs? Cities in Michigan with the most Data Bi Engineer job openings:
Data Bi Engineer jobs near you

Data / BI Architect

Tech Tammina LLC

Pontiac, MI • On-site

Contractor

Posted 24 days ago

Job description

Role: Data / BI Architect

Location: Pontiac, MI

Duration: 12Months +

About role:

Data Business Intelligence (BI) Architect role is a hybrid of data architecture, engineering & business strategy, bridging the gap between tech data solutions & business objectives. Designs, develops & maintains the overall data strategy ensuring the County data in scope is accessible, reliable & secure for analysis and decision-making. The right candidate has experience in architecting data solutions that can be used for descriptive, diagnostic, predictive & prescriptive analytic solutions.

KEY RESPONSIBILITIES:

•       Stakeholder Collaboration: Work closely with business & IT stakeholders to gather req & translate business needs into tech specifications, including identification of data sources.

•       Data Arch Design & Data Modeling: Architect & implement scalable, secure & efficient data solutions, including data warehouses, data lakes, and/or data marts.

•       Design conceptual, logical & physical data models.

•       Tool and Platform Selection: Evaluate, recommend & implement tools aligned with recommended architecture, including visualization tools aligned with business needs.

•       ETL/ELT Pipeline Mgt: Design, develop & test data pipelines, integrations to source mgt & ETL / ELT processes to move data from various sources into the data warehouse.

•       Data Catalog & Metadata Mgt: Design, create & maintain an enterprise-wide data catalog, automating metadata ingestion, establishing data dictionaries, and ensuring that all data assets are properly documented & tagged.

•       Data Governance and Discovery: Enforce data governance policies through the data catalog, ensuring data quality, security & compliance.

•       Enable self-service data discovery for users by curating & organizing data assets in an intuitive way.

•       Performance Optimization: Monitor & optimize BI systems & data pipelines to ensure high performance, reliability & cost-effectiveness.

•       Technical Leadership: Provide technical guidance & mentorship across the organization, establishing best practices for data mgt & BI development.

Environment:

•       Role incl. defining data platform tech stack. Example tech below; not required to have experience in all.

•       Data Platforms: DW & lake concepts incl. dimensional modeling & cloud services (S3, AWS Redshift, RDS, Azure Data Lake Storage, Synapse Analytics, BigQuery, Databricks, Snowflake, Informatica);

•       Databases: SQL & relational/non-relational (SQL Server, Oracle, PostgreSQL, MongoDB);

•       BI Tools: Power BI, Business Objects, Tableau, Crystal, Looker;

•       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: Python, Keras, Scikit-learn, R, XML;

•       ML/DL/Analytic Engines: TensorFlow, PyTorch, Trillium, Apache Spark;

•       Modeling Tools: MS Visio, ER/Studio, PowerDesigner;

•       Source systems incl. on-prem, cloud, & SaaS;