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Sql Python Excel Power Bi Tableau Jobs in Center Line, MI

Tech Tammina LLC

Data / BI Architect

Pontiac, MI · On-site

... SQL Server, Oracle, PostgreSQL, MongoDB); • BI Tools: Power BI, Business Objects, Tableau ... Python, Keras, Scikit-learn, R, XML; • ML/DL/Analytic Engines: TensorFlow, PyTorch, Trillium ...

Stellantis

Ontology Engineer

Auburn Hills, MI · On-site

... SQL and Python to support our enterprise analytics architecture. You will work across platforms such as Snowflake, Palantir Foundry, Power BI, and potentially Databricks, helping the team evolve ...

Tech Tammina LLC

Data Analyst

Warren, MI · On-site

Microsoft Office Suite (Excel, Word, PowerPoint) * Visual Basic for Applications (VBA) * Tableau and Power BI * Databricks, Python (Scripting), Jupyter, Spark, Hue * Oracle PL/SQL, Oracle DBMS ...

OneMagnify

Analytics and Insights Lead

Detroit, MI · On-site

Hands-on expertise with SQL, Python, and visualization tools (e.g., Power BI, Tableau) Benefits We believe great work happens when people have the support and flexibility they need to thrive. Our ...

Cloud BC Labs

GCP Data Engineer

Dearborn Heights, MI · On-site

... SQL, Python, ETL/ELT tools, and BI tools. This role will collaborate closely with product owners ... Familiarity with BI tools such as Qlik Sense, Power BI, or Looker. * Data Warehousing:

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How much do sql python excel power bi tableau jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for sql python excel power bi tableau in Center Line, MI is $52.82, according to ZipRecruiter salary data. Most workers in this role earn between $43.56 and $62.31 per hour, depending on experience, location, and employer.

What is the difference between Sql Python Excel Power Bi Tableau vs Data Analyst?

AspectSql Python Excel Power Bi TableauData Analyst
Required SkillsSQL, Python, Excel, Power BI, TableauData analysis, SQL, Excel, visualization tools
Work EnvironmentBusiness intelligence, data visualization, reportingData interpretation, reporting, business insights
Industry UsageTech, finance, marketing, consultingFinance, healthcare, retail, marketing

Sql Python Excel Power Bi Tableau professionals focus on data extraction, analysis, and visualization using specific tools. Data Analysts interpret data to provide insights, often using similar skills but with a broader focus on business decision-making. While both roles require SQL and Excel, the former emphasizes technical data manipulation and visualization tools, whereas Data Analysts focus on understanding data trends and presenting actionable insights.

What are SQL, Python, Excel, Power BI, and Tableau jobs?

Jobs that require skills in SQL, Python, Excel, Power BI, and Tableau typically involve working with data analysis, data visualization, and business intelligence. Professionals in these roles use SQL to manage and query databases, Python for data processing and automation, Excel for organizing and analyzing data, and Power BI or Tableau to create interactive dashboards and reports. These roles are common in industries like finance, healthcare, marketing, and technology, where data-driven decision-making is essential. Common job titles include Data Analyst, Business Intelligence Analyst, and Data Scientist.

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

To thrive as a Data Analyst, you need strong analytical skills, proficiency in SQL and Python for data manipulation, and a solid understanding of Excel for data organization and calculations. Familiarity with data visualization tools like Power BI and Tableau, as well as relevant certifications such as Microsoft Certified: Data Analyst Associate, are highly valuable. Attention to detail, problem-solving abilities, and effective communication skills help translate complex data findings into actionable insights for stakeholders. These skills are crucial for extracting meaningful information from data, driving business decisions, and presenting results clearly to both technical and non-technical audiences.

How do professionals using SQL, Python, Excel, Power BI, and Tableau typically collaborate within data teams?

Professionals skilled in SQL, Python, Excel, Power BI, and Tableau often work closely with data analysts, data engineers, and business stakeholders. They collaborate by gathering requirements, extracting and transforming data (using SQL and Python), and then visualizing insights (with Power BI and Tableau) or conducting ad-hoc analysis in Excel. Regular communication and sharing of dashboards or reports are common, as is peer review of data models and code. This collaborative environment helps ensure accurate, actionable insights for the organization.
What job categories do people searching Sql Python Excel Power Bi Tableau jobs in Center Line, MI look for? The top searched job categories for Sql Python Excel Power Bi Tableau jobs in Center Line, MI are:
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Sql Python Excel Power Bi Tableau jobs near you
Data / BI Architect

Data / BI Architect

Tech Tammina LLC

Pontiac, MI • On-site

Contractor

Re-posted 10 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;