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Sr Director Data Analytics Jobs (NOW HIRING)

Reporting to the Managing Director, Digital Investigations & Cyber Risk, the Director of Data Analytics supports investigations, risk assessments, and expert witness matters across the firm including ...

Director, Data Analytics

Manhattan, NY · On-site

$150K - $175K/yr

Reporting to the Managing Director, Digital Investigations & Cyber Risk, the Director of Data Analytics supports investigations, risk assessments, and expert witness matters across the firm including ...

We are seeking an experienced and strategic Director of Data Analytics to take the helm of a high-performing team of data analytics professionals. This critical leadership role will be centered on ...

Reporting to the Managing Director, Digital Investigations & Cyber Risk, the Director of Data Analytics supports investigations, risk assessments, and expert witness matters across the firm including ...

Hussmann is a global leader in commercial refrigeration equipment, and they are seeking a Director of Data & Analytics to define and execute their enterprise data, analytics, and AI strategy. This ...

We are looking for a Director of Data and Analytics to join our team! You will lead data and analytics at Prenuvo, building this function from where we stand today (a lean and focused team serving ...

We're looking for a Director of Data & Analytics to own the data foundation that powers both businesses, from pipelines and BI tools to the agents our team queries data through, and the strategic ...

We are looking for a Director of Data and Analytics to join our team! You will lead data and analytics at Prenuvo, building this function from where we stand today (a lean and focused team serving ...

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Sr Director Data Analytics information

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How much do sr director data analytics jobs pay per hour?

As of Jun 10, 2026, the average hourly pay for sr director data analytics in the United States is $56.81, according to ZipRecruiter salary data. Most workers in this role earn between $46.63 and $67.31 per hour, depending on experience, location, and employer.

What does a Sr Director of Data Analytics do?

A Sr Director of Data Analytics leads an organization's data analytics strategy and oversees large teams responsible for collecting, analyzing, and interpreting complex data to support business decision-making. They collaborate with other executives to align analytics initiatives with business goals, ensure data integrity, and implement advanced tools and technologies. This role involves managing budgets, mentoring analytics professionals, and communicating key insights to stakeholders to drive organizational success.

What are some common challenges faced by a Sr Director of Data Analytics, and how can they be addressed?

A Sr Director of Data Analytics often faces challenges such as aligning data strategy with business goals, managing cross-functional teams, and ensuring data quality and governance. Balancing the need for quick insights with rigorous data validation, as well as fostering a data-driven culture across departments, can be complex. These challenges can be addressed by establishing clear communication channels, setting robust data governance policies, and continuously upskilling the analytics team to adapt to evolving technologies and business needs.

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

To thrive as a Sr Director Data Analytics, you need advanced expertise in data analysis, statistical modeling, and data strategy, typically supported by a degree in a quantitative field and significant leadership experience. Familiarity with data visualization tools (like Tableau or Power BI), analytics platforms (such as SQL, Python, R), and data governance frameworks is essential, along with certifications like Certified Analytics Professional (CAP) being advantageous. Strategic thinking, exceptional communication, and the ability to influence and lead cross-functional teams are vital soft skills. These capabilities ensure effective data-driven decision-making, foster innovation, and drive organizational success.

What is the difference between Sr Director Data Analytics vs Data Analytics Manager?

AspectSr Director Data AnalyticsData Analytics Manager
ResponsibilitiesOversees multiple teams, sets strategic analytics goals, and influences company-wide data initiatives.Manages analytics projects, leads a team of analysts, and ensures project delivery.
Required CredentialsBachelor’s or Master’s in Data Science, Analytics, or related; extensive experience in data leadership roles.Bachelor’s or Master’s in relevant fields; experience in data analysis and team management.
Work EnvironmentStrategic, cross-departmental, executive-level collaboration.Operational, project-focused, team management within analytics teams.

The main difference between a Sr Director Data Analytics and a Data Analytics Manager lies in scope and strategic influence. The Sr Director typically oversees multiple teams, sets long-term data strategies, and works closely with executive leadership. In contrast, the Data Analytics Manager focuses on managing projects and day-to-day team operations. Both roles require strong analytical credentials, but the Sr Director’s role is more strategic and organization-wide.

More about Sr Director Data Analytics jobs
What cities are hiring for Sr Director Data Analytics jobs? Cities with the most Sr Director Data Analytics job openings:
What states have the most Sr Director Data Analytics jobs? States with the most job openings for Sr Director Data Analytics jobs include:
Infographic showing various Sr Director Data Analytics job openings in the United States as of June 2026, with employment types broken down into 86% Full Time, and 14% Part Time. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $118,171 per year, or $56.8 per hour.
Director, Data & Analytics

Other

Posted 10 days ago


Job description

JOB TITLE: Director, Data & Analytics

LOCATION: Corporate Headquarters Johnstown, CO

(Position is hybrid but must be commutable/accessible to corporate headquarters in Northern Colorado.)

REPORTS TO: Vice President, Information Technology

FLSA STATUS: Salaried, Non-Exempt

FUNCTION: Responsible for the technical leadership, delivery oversight, prioritization, and operational maturity of the companys data warehouse, pipelines, semantic models/cubes, and data experience layers.

ESSENTIAL DUTIES AND RESPONSIBILITIES:

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Other duties may be assigned.

  • Leadership and Team Management

    • Lead, coach, and develop the Data & Analytics team, including developers and related technical resources.

    • Provide clear direction, work planning, prioritization, and performance management for the team.

    • Establish team standards, operating rhythms, delivery practices, and documentation expectations.

    • Serve as escalation point and technical backstop for warehouse, pipeline, model/cube, and reporting work.

    • Build cross-training and redundancy so function is sustainable and not dependent on any one individual.

  • Data & Analytics Strategy and Delivery

    • Own the delivery and support of enterprise data and analytics solutions, including:

      • data warehouse architecture and administration

      • data integration and pipelines

      • semantic models and cubes

      • enterprise reporting and dashboards

    • Guide solution design to ensure data products are scalable, secure, maintainable, and business-aligned.

    • Oversee the intake, assessment, prioritization, and execution of analytics initiatives.

    • Maintain a roadmap for data and analytics capabilities that supports operational, financial, risk, HR, environmental, and executive reporting needs.

    • Ensure analytics delivery is treated as an enterprise capability serving the whole business, rather than a narrow sub-function of IT or any single department.

  • Technical Leadership

    • Provide technical oversight and practical guidance in:

      • enterprise data warehousing

      • ETL/ELT and data pipeline design

      • dimensional modeling and semantic layer design

      • cubes and analytical data structures

    • Power BI datasets, reports, dashboards, governance, and performance tuning

    • Review architecture and design decisions to promote reliability, usability, scalability, and supportability.

    • Partner closely with Software Development to define, obtain, and improve operational data sources needed for analytics solutions.

    • Work with IT leadership to establish standards for data quality, metadata, naming, lineage, security, and lifecycle management.

    • Support troubleshooting and continuity of delivery by being capable of guiding, reviewing, and backing up the teams technical work when needed.

  • Business Engagement and Relationship Management

    • Translate business goals into practical data and analytics solutions.

    • Partner with stakeholders across the company to clarify needs, define requirements, and manage expectations.

    • Serve as a primary liaison between technical teams and business partners for enterprise reporting and analytics initiatives.

    • Help stakeholders understand priorities, tradeoffs, dependencies, and delivery timelines.

  • Project Management, Analysis, and Quality

    • Apply strong project management discipline to analytics initiatives, including planning, scope definition, milestone tracking, issue management, and status communication.

    • Perform or oversee business analysis activities such as requirements gathering, process review, use-case development, and solution validation.

    • Establish and enforce QA practices for data and analytics solutions, including testing strategy, reconciliation, validation, user acceptance support, and release readiness.

    • Promote high-quality outputs by ensuring reports, models, and pipelines are accurate, understandable, and fit for business use.

  • Advanced Analytics, AI, and Enablement

    • Support the companys use of Microsoft Fabric, Foundry, Azure ML Studio, and advanced analytics tools.

    • Assist power users in applying machine learning, AI, and automation in practical business scenarios.

    • Enable and support technical power users across the company in their effective and responsible use of analytics, AI, and self-service tools.

    • Help define appropriate governance, support boundaries, and best practices for business-facing analytical and AI capabilities.

QUALIFICATIONS:

  • Required Education and Experience

    • Bachelors degree in Computer Science, Data Analytics, or a related technical field, or equivalent combination of education and experience.

    • Strong (5+ years) experience in data warehousing, analytics, business intelligence, and related IT disciplines.

    • Strong (5+ years) experience managing technical teams, leads, and major cross-functional initiatives.

    • Demonstrated experience delivering enterprise data and analytics solutions in a complex environment.

  • Required Technical Knowledge and Skills

    • Strong working knowledge of:

      • data warehousing concepts and platforms

      • data integration, ETL/ELT, and pipeline orchestration

      • dimensional modeling and semantic modeling

      • cubes and analytical structures

      • Dataset design, report development, and performance optimization

    • Ability to review technical designs, guide architecture decisions, and coach developers on best practices.

    • Strong understanding of data quality, data governance, security, and supportability considerations.

    • Experience working with operational system data and partnering with software development teams.

  • Required Professional Skills

    • Strong project management skills, including planning, prioritization, coordination, and delivery oversight.

    • Strong business analysis skills, including requirements elicitation, process understanding, and solution definition.

    • Strong QA mindset with experience in validation, testing, and release quality.

    • Excellent verbal and written communication skills with the ability to work effectively with both technical and business audiences.

    • Ability to build trust, influence decisions, and navigate dependencies across functions.

    • Strong problem-solving ability, sound judgment, and attention to detail.

  • Preferred Qualifications

    • Experience with Microsoft Foundry, OneLake, Azure ML Studio and similar machine learning platforms.

    • Experience supporting AI-enabled solutions, self-service analytics, or enterprise data enablement.

    • Experience with large-scale, industrial, operations-heavy, multi-site production animal agricultural.

    • Familiarity with change management and user enablement for analytics adoption.

  • Key Competencies

    • Technical leadership

    • Team leadership and coaching

    • Enterprise thinking

    • Cross-functional collaboration

    • Business partnership

    • Project execution

    • Analytical problem solving

    • Quality orientation

    • Communication and influence

    • Continuous improvement

Success Measures

  • a stable, well-led Data & Analytics function with clear priorities and accountability

  • improved alignment between analytics delivery and business needs

  • reliable and scalable warehouse, pipeline, model, cube, and Power BI solutions

  • effective partnership with IT leadership, business stakeholders, and power users/analysts

  • stronger quality, documentation, and support practices

  • increased organizational capability in analytics, AI, and power-user enablement

PHYSICAL DEMANDS:

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Office work will include, but are not limited to: Reaching, bending and sitting for a prolonged period of time at a work station or desk operating and viewing systems, documents, and calculator. On occasion moving and carrying boxes for storage.

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