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Manager of Data Analytics

San Francisco, CA · On-site

$200K/yr

Position: Manager of Data Analytics Location:345 Schwerin Street, San Francisco, CA 94134 ... Position also supervises 4 employees. Educ./experience: Master's degree or foreign equivalent in ...

Troy University

Lecturer - Data Analytics

Troy, AL · On-site

Posting Details Position Information Posting Number F0997P Position Title Lecturer - Data Analytics ... have supervisory responsibility? No Posting Date 04/08/2026 Closing Date Open Until Filled Yes ...

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Data Analytics Supervisor information

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$31K

$97.1K

$172K

How much do data analytics supervisor jobs pay per year?

As of Jun 22, 2026, the average yearly pay for data analytics supervisor in the United States is $97,145.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,000.00 and $125,500.00 per year, depending on experience, location, and employer.

What does a data analyst supervisor do?

A data analyst supervisor oversees a team of data analysts, ensuring accurate data collection, analysis, and reporting. They develop data strategies, review analysis work, and collaborate with other departments to support decision-making, often using tools like SQL, Excel, or data visualization software. Strong leadership and communication skills are essential for managing projects and guiding team members.

What is the highest paying job in data analytics?

The highest paying roles in data analytics typically include Data Science Directors, Chief Data Officers, and senior Data Analytics Managers, especially those overseeing large teams or strategic initiatives. These positions often require advanced skills in machine learning, big data tools, and leadership, with salaries reaching into the high six or seven figures for experienced professionals in large organizations.

What is the difference between Data Analytics Supervisor vs Data Analyst?

AspectData Analytics SupervisorData Analyst
CredentialsBachelor's or Master's in Data Science, Analytics, or related field; often requires experience in leadership rolesBachelor's degree in Data Science, Statistics, or related field; entry to mid-level experience
Work EnvironmentOversees teams, manages projects, collaborates with managementPerforms data analysis, reports findings, supports decision-making
Employer & Industry UsageUsed across industries like finance, healthcare, tech; common in organizations with analytics teamsFound in similar industries; often entry to mid-level role supporting analytics projects

The main difference is that Data Analytics Supervisors oversee teams and manage projects, while Data Analysts focus on analyzing data and generating reports. Supervisors typically have more experience and leadership responsibilities, whereas Data Analysts are more hands-on with data processing and analysis tasks.

What does a Data Analytics Supervisor do?

A Data Analytics Supervisor oversees a team of data analysts, ensuring they collect, process, and analyze data effectively to support business decisions. They are responsible for managing projects, setting goals, and providing technical guidance to their team. Additionally, they collaborate with other departments to identify data needs, develop strategies, and present insights to leadership. The role requires strong analytical, communication, and leadership skills.

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

To thrive as a Data Analytics Supervisor, you need strong analytical abilities, leadership experience, proficiency in statistical analysis, and a relevant degree in data science, statistics, or a related field. Familiarity with tools like SQL, Python, R, and business intelligence platforms (e.g., Tableau, Power BI) is typically required, along with experience managing data projects and teams. Excellent communication, problem-solving, and team management skills distinguish top performers in this role. These competencies are crucial for translating data insights into actionable strategies, guiding teams effectively, and ensuring the organization's data-driven decision-making success.

How does a Data Analytics Supervisor typically collaborate with cross-functional teams within an organization?

A Data Analytics Supervisor often works closely with departments such as marketing, finance, operations, and IT to identify analytical needs and deliver actionable insights. They facilitate meetings to understand business objectives, translate requirements into data-driven solutions, and ensure that analytics projects align with broader organizational goals. Effective communication and the ability to translate complex data findings into clear, actionable recommendations are critical for fostering strong interdepartmental collaboration.

What are the 5 C's of data analytics?

The 5 C's of data analytics are commonly considered to be Completeness, Consistency, Accuracy, Timeliness, and Uniqueness. These principles help data analysts and supervisors ensure data quality and reliability for accurate insights and decision-making.

Is AI replacing data analysts?

AI is transforming the role of data analysts by automating routine tasks such as data cleaning and basic analysis, allowing analysts to focus on more complex insights and strategic decision-making. While AI tools can enhance efficiency, skilled data analysts are still essential for interpreting results, developing models, and providing context-specific recommendations. The role is evolving rather than being replaced entirely, emphasizing the importance of skills in data visualization, programming, and domain knowledge.
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Data Analytics Supervisor jobs near you
Infographic showing various Data Analytics Supervisor job openings in the United States as of June 2026, with employment types broken down into 91% Full Time, and 9% Part Time. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution, with an average salary of $97,145 per year, or $46.7 per hour.

Data Analytics Engineer

Mutual of Enumclaw Insurance Company

Enumclaw, WA • On-site

$140K - $171K/yr

Other

Posted 9 days ago

Job description

Overview
Founded in 1898, Mutual of Enumclaw is a people-first insurer rooted in community, recognized as Washington's Best Company to Work For for the 14th consecutive year, and proudly serving individuals, families, farms, and businesses through local independent agents across the West.
The Data Analytics Engineer bridges the gap between raw data and business insights by designing, building, and governing analytics-ready data assets across the P&C insurance value chain - Underwriting, Actuarial, Claims, Product, Distribution, and Finance - and all lines of business (Personal, Commercial, and Farm). Translating insurance business logic into governed, scalable data models, the Data Analytics Engineer partners with stakeholders to deliver trusted reporting and analytics solutions and plays a key role in advancing Mutual of Enumclaw's Snowflake-based medallion architecture and enabling data-driven decision-making across the company.
Location: Remote, with preference given to those residing in WA, OR, ID, MT, WY, AZ, or UT. (Candidates must be able to work during our core Pacific Standard Time business hours and have high-speed internet - an internet speed test is required.)
Hiring Range: $140,891 - $157,545
Salary Range: $140,891 - $171,631
*The hiring range represents Mutual of Enumclaw's current hiring pay scale for this role. Mutual of Enumclaw reserves the right to modify or update this range any time. Exact compensation may vary based on skills and experience. Compensation is only one part of our entire total rewards package. To see some of the benefits and perks we offer, please click here.
Responsibilities
Supervisory Responsibilities:
  • None.

Responsibilities:
Business Partnership & Delivery
  • Partner with stakeholders across Product, Actuarial, Underwriting, Claims, Finance, and Distribution to gather requirements and define KPIs, reporting needs, and data specifications
  • Design, build, and maintain dashboards, reports, and visualizations in Sigma, Power BI, or equivalent BI platforms that deliver trusted insights to underwriters, actuaries, claims leaders, distribution partners, and executive leadership
  • Translate business needs into scalable data solutions, dashboards, and analyses that support strategic and operational decision-making
  • Support recurring and ad hoc reporting, including financial, operational, and executive reporting

Data Modeling & Engineering
  • Design, build, and maintain data models, transformations, and semantic layers within a Snowflake-based medallion architecture
  • Develop scalable, testable data pipelines using SQL and dbt (or equivalent tools)
  • Integrate data from internal and external sources (e.g., policy systems, Salesforce, HubSpot)
  • Enable self-service analytics by designing semantic layers and certified data products that allow business users to answer their own questions without engineering intervention

Data Governance & Quality
  • Define and enforce data governance standards, including data definitions, access controls, and metadata management
  • Validate and test data outputs to ensure accuracy and reliability
  • Monitor data performance and continuously improve data products based on user feedback

Agile Delivery & Support
  • Collaborate with Product Owners and participate in Agile ceremonies (planning, refinement, sprint reviews)
  • Define acceptance criteria and deliver high-quality data products
  • Provide production support and troubleshoot data/reporting issues as needed

Qualifications
Required Skills/Abilities:
  • P&C insurance industry experience required, with demonstrated understanding of the insurance value chain from underwriting through claims and fluency in core insurance concepts, terminology, and reporting metrics.
  • Strong experience designing, building, and publishing dashboards and reports in Sigma, Power BI, or equivalent BI platforms, including data modeling for self-service consumption required
  • Strong experience with cloud data warehouses (Snowflake preferred) and transformation tools such as dbt
  • Proficiency in SQL; working knowledge of Python or similar scripting languages preferred
  • Solid understanding of dimensional modeling, ELT processes, and modern data architectures (e.g., medallion/lakehouse)
  • Experience building or migrating to a modern data platform (e.g., legacy data warehouse to Snowflake/medallion architecture) preferred.
  • Knowledge of data integration methods (APIs, flat files, semi-structured data) and cloud platforms (AWS or equivalent)
  • Strong communication skills with the ability to translate technical concepts for business audiences
  • Experience working in Agile environments

Education and Experience:
  • Bachelor's degree in data science, computer science, statistics, or a related field (or equivalent experience)
  • 5+ years of experience in data analytics, data engineering, or related roles
  • Experience working with data systems, pipelines, and reporting solutions
  • Experience in P&C insurance and familiarity with insurance data and metrics required (e.g., premium, loss, reserving)
  • Working knowledge of insurance source systems such as Guidewire (PolicyCenter, ClaimCenter, BillingCenter), POINT, Duck Creek, or equivalent policy and claims administration platforms preferred

Physical Requirements:
  • Prolonged periods of sitting at a desk and working on a computer, including video conferencing.

Apply