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Part Time Azure Synapse Analytics Jobs (NOW HIRING)

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We are seeking an experienced Part-Time Data Analyst to support a federal agency in developing ... Support cloud-based analytics environments utilizing AWS or Azure services, including Databricks ...

Senior Data Analyst (part-time)

Arlington, VA · On-site

$99K - $125K/yr

... including Data Analytics Expressions (DAX), data Mash-up(M), and Microsoft Power Platform (e.g., Power BI, Power Apps, Power Automate, etc.). * Knowledge of AWS or Azure Services, including ...

Data Analyst IV

Atlanta, GA · On-site

$50 - $60/hr

NACI Data Engineer & Analyst, Part-time with Full Time Potential AMDEX.ai The Art of Data Science ... Design, build, and integrate secure data workflows across Palantir Foundry, Azure Data Factory ...

Professeur a temps-partiel regulier / Regular Part-Time Professor Date Posted (YYYY/MM/DD): 2026/05 ... Knowledge of Big Data Analytics implementations by cloud providers, especially MS Azure.

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Part Time Azure Synapse Analytics information

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How much do part time azure synapse analytics jobs pay per year?

As of Jun 15, 2026, the average yearly pay for part time azure synapse analytics in the United States is $103,000.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,500.00 and $122,500.00 per year, depending on experience, location, and employer.

What are part-time Azure Synapse Analytics professionals?

Part-time Azure Synapse Analytics professionals are individuals who work fewer than full-time hours to help organizations manage, analyze, and integrate large volumes of data using Microsoft Azure Synapse Analytics. Their responsibilities often include building data pipelines, optimizing queries, and developing analytics solutions within the Synapse workspace. These professionals may specialize in data engineering, business intelligence, or data analysis, and they typically collaborate with other IT and business teams to ensure efficient data-driven decision-making. Part-time roles offer flexibility for both employers and employees, making them ideal for project-based or consulting work where full-time staff are not required.

What is the difference between Part Time Azure Synapse Analytics vs Part Time Data Analyst?

AspectPart Time Azure Synapse AnalyticsPart Time Data Analyst
Required SkillsAzure Synapse, SQL, data integration, analytics toolsExcel, SQL, data visualization, reporting
CertificationsAzure certifications (e.g., DP-420)None mandatory, often Excel or Tableau certifications
Work EnvironmentCloud-based, data warehouses, large datasetsOffice or remote, data interpretation and reporting
Industry UsageData engineering, cloud analytics projectsBusiness reporting, market analysis

Part Time Azure Synapse Analytics focuses on cloud-based data integration and analytics using Azure tools, requiring technical skills and certifications. In contrast, Part Time Data Analysts primarily interpret data, create reports, and visualize insights, often with less emphasis on cloud platforms. Both roles are essential in data-driven industries but serve different functions and skill sets.

What are the key skills and qualifications needed to thrive as a Part Time Azure Synapse Analytics professional, and why are they important?

To excel as a Part Time Azure Synapse Analytics professional, you need a solid background in data engineering, SQL, and cloud data platforms, often supported by experience or certification in Microsoft Azure. Familiarity with Azure Synapse Studio, Power BI, and data integration tools is typically required. Strong analytical thinking, problem-solving, and effective communication skills set candidates apart in this role. These competencies enable efficient data management, insightful analytics, and collaboration on business intelligence initiatives within organizations.

What are the main challenges faced by professionals working part-time with Azure Synapse Analytics?

Part-time Azure Synapse Analytics professionals often encounter challenges in keeping up with rapidly evolving cloud technologies and ensuring alignment with full-time team members' schedules. Since projects can be data-intensive and require timely collaboration, effective communication and time management are crucial. Additionally, part-time roles may require prioritizing key tasks, as there might be less time available for in-depth troubleshooting or continuous monitoring of data pipelines. However, many teams use collaborative tools and clear documentation to help part-time members stay engaged and productive.
What are the most commonly searched types of Azure Synapse Analytics jobs? The most popular types of Azure Synapse Analytics jobs are:
What states have the most Part Time Azure Synapse Analytics jobs? States with the most job openings for Part Time Azure Synapse Analytics jobs include:
Part-Time Data Analyst

Part-Time Data Analyst

The Midtown Group

Arlington, VA • On-site

$65/hr

Part-time

Medical, Dental

Posted 6 days ago

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Job description

We are seeking an experienced Part-Time Data Analyst to support a federal agency in developing, maintaining, and enhancing enterprise data analytics, reporting, and business intelligence solutions. The ideal candidate will possess strong technical expertise in data analysis, data engineering, visualization, and cloud-based analytics platforms while effectively collaborating with business stakeholders and technical teams to deliver actionable insights and innovative solutions.  This role with be 10-20 hours/week and require occasional on-site meetings.
This role requires a highly skilled professional who can translate complex business requirements into technical solutions, develop advanced analytics products, and support enterprise data initiatives utilizing modern cloud and business intelligence technologies.
Key Responsibilities

  • Design, develop, and maintain data analytics solutions, dashboards, reports, and visualizations using industry-standard tools and technologies.
  • Utilize programming languages including SQL, Python, R, and JavaScript to develop datasets, automate processes, and support analytical initiatives.
  • Develop and maintain business intelligence solutions using Microsoft Power Platform technologies, including Power BI, Power Apps, and Power Automate.
  • Create and maintain DAX and Power Query (M) code for data transformation, modeling, and reporting.
  • Collaborate with agency stakeholders to identify business and technical requirements and translate them into technical designs and implementation plans.
  • Engineer data solutions through prototyping, proof-of-concept development, testing, and full production implementation.
  • Analyze and support Extraction, Transformation, and Load (ETL) processes and data integration strategies.
  • Support cloud-based analytics environments utilizing AWS or Azure services, including Databricks, Data Factory, and Data Lake technologies.
  • Serve as a liaison between business users, database administrators, and IT support teams to facilitate effective communication and solution delivery.
  • Troubleshoot and support existing applications, reports, dashboards, and data environments.
  • Review, analyze, modify, test, debug, and document existing code, reports, and analytical products.
  • Evaluate and document data security, continuity of operations, and compliance requirements for analytical systems.
  • Ensure compatibility between software, hardware, and data environments while supporting system design reviews and technical briefings.
  • Develop comprehensive technical documentation, including requirements, methodologies, data sources, business rules, and deployment procedures.
  • Provide guidance and mentoring to team members regarding data quality, data access, storage, analytics tools, and best practices.
  • Assist with training initiatives, workshops, and presentations for both technical and non-technical audiences.
  • Support data governance, data warehousing, relational database management, and data quality initiatives.
  • Ensure adherence to software development lifecycle (SDLC) processes, quality standards, and security guidelines.


Required Qualifications

  • US Citizenship Required
  • Bachelor's degree in Computer Science, Information Technology, Data Analytics, Data Science, or a related technical field.
  • Minimum of 7 years of experience developing solutions using SQL, Python, R, JavaScript, or comparable programming languages.
  • Minimum of 3 years of experience working with Microsoft Power Platform technologies, including Power BI, Power Apps, and Power Automate.
  • Minimum of 1 year of experience working with cloud analytics services such as AWS or Azure, including Databricks, Data Factory, and Data Lake solutions.
  • Demonstrated experience developing analytical models, dashboards, reports, and business intelligence solutions that drive measurable business outcomes.
  • Advanced proficiency in SQL and relational database technologies.
  • Strong experience with ETL development, data integration, and data transformation methodologies.
  • Expertise in DAX, Power Query (M), and business intelligence reporting frameworks.
  • Experience with data warehousing, data governance, data quality, and data management best practices.
  • Knowledge of ODBC connection strings and external data source connectivity protocols.
  • Experience working with both structured and unstructured data sources.
  • Familiarity with cloud-based analytics and data engineering platforms.
  • Strong understanding of software development lifecycle methodologies and quality assurance processes.


The Midtown Group is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. We are a small, woman-owned business certified by the Women’s Business Enterprise National Council (WBENC). Operating from our headquarters in Washington, DC, we provide trusted staffing services nationwide. Our clients include thousands of the most prestigious Fortune 500 companies, law firms, financial organizations, tech innovators, non-profits, and lobbying firms, as well as federal, state and local government agencies.