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Director Of Data Strategy Jobs (NOW HIRING)

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$54K

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How much do director of data strategy jobs pay per year?

As of Jun 17, 2026, the average yearly pay for director of data strategy in the United States is $154,873.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,000.00 and $189,500.00 per year, depending on experience, location, and employer.

What does a Director of Data Strategy do?

A Director of Data Strategy is responsible for developing and implementing an organization's overall data vision and strategy. They oversee data management, governance, analytics, and ensure data aligns with business goals. This role involves collaborating with executive leadership, managing data teams, and driving initiatives that leverage data to improve business performance and gain competitive advantage. They also ensure compliance with data regulations and help foster a data-driven culture within the organization.

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

To thrive as a Director Of Data Strategy, you need expertise in data analytics, business intelligence, and strategic planning, typically supported by an advanced degree in data science, analytics, or a related field. Familiarity with data management tools, cloud platforms (such as AWS or Azure), and certifications like Certified Analytics Professional (CAP) are often required. Strong leadership, communication, and problem-solving skills help drive cross-functional collaboration and align data initiatives with business goals. These abilities are critical for leveraging data insights to inform decision-making, foster innovation, and achieve organizational objectives.

What are some common challenges faced by Directors of Data Strategy when aligning data initiatives with organizational goals?

Directors of Data Strategy often encounter challenges such as bridging communication gaps between technical data teams and business stakeholders, ensuring data initiatives directly support overall business objectives, and managing change across departments. Balancing the need for robust data governance with the agility required for innovation is also a frequent concern. Success in this role relies on strong cross-functional collaboration, clear communication of data value, and continuous adaptation to evolving business needs.
More about Director Of Data Strategy jobs
What cities are hiring for Director Of Data Strategy jobs? Cities with the most Director Of Data Strategy job openings:
What are the most commonly searched types of Of Data Strategy jobs? The most popular types of Of Data Strategy jobs are:
What states have the most Director Of Data Strategy jobs? States with the most job openings for Director Of Data Strategy jobs include:
Infographic showing various Director Of Data Strategy job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $154,873 per year, or $74.5 per hour.
Director of Data Strategy

Director of Data Strategy

RaceTrac Petroleum, Inc.

Atlanta, GA • On-site

Full-time

Posted 23 days ago


RaceTrac rating

4.7

Company rating: 4.7 out of 10

Based on 194 frontline employees who took The Breakroom Quiz

36th of 47 rated convenience stores


Job description

RaceTrac Company Overview
Job Description:
Director, Data Strategy
Role Summary
The Director of Data Strategy shapes RaceTrac's enterprise-wide vision for how data is governed, managed, activated, and measured. This leader ensures that data becomes a strategic asset-fueling revenue growth, operational efficiency, regulatory compliance, and exceptional guest experiences. Working across Technology, Analytics, Product, Finance, and Business Units, this role builds the roadmap, operating model, and culture needed to unlock the full value of data at scale.
Key Responsibilities
• Define a multi-year enterprise data strategy aligned to business goals, including prioritization models and investment frameworks.
• Build and operationalize a scalable data operating model with clear ownership, standards, and funding structures.
• Lead enterprise data governance across privacy, security, lineage, quality, retention, and AI risk.
• Implement data stewardship, issue management, and measurable defect-reduction processes.
• Oversee the lifecycle of high-value data products and partner with engineering/analytics to define requirements and success metrics.
• Drive data literacy and self-service adoption across business teams.
• Build business cases and track ROI for data initiatives; lead quarterly portfolio reviews with Finance and BU leaders.
• Align with Enterprise Data Architecture on platform strategy, including lakehouse/warehouse, MDM, catalog, governance tools, and AI/ML platforms.
• Promote standardized data models and interoperability across domains (finance, customer, product, operations, HR).
• Establish responsible AI guardrails and ensure data readiness for ML/GenAI use cases.
• Prioritize and incubate analytics and AI use cases with clear problem statements and measurable outcomes.
• Lead executive-level communications, socialize strategy, and support change management across the enterprise.
Success Measures (First 3-6 and 6-12 Months)
3-6 Months:
  • Deliver an enterprise data strategy and operating model proposal.
  • Stand up initial governance processes, including stewardship roles and issue-management workflows.
  • Establish baseline data quality, risk, and value-tracking metrics.
  • Build strong cross-functional relationships with Technology, Finance, Product, and BU leaders.

6-12 Months:
  • Launch prioritized data products with defined success metrics and adoption plans.
  • Demonstrate measurable improvements in data quality, lineage visibility, and governance compliance.
  • Implement value-realization frameworks and complete the first portfolio review cycle.
  • Advance AI/analytics readiness, including responsible AI guardrails and prioritized use-case incubation.

Required Skills & Experience
• Bachelor's or Master's degree in Data Management, Computer Science, Information Systems, Business, or related field.
• 7+ years of experience in data management, governance, and analytics, including 5+ years in leadership roles.
• Strong understanding of data governance frameworks, data quality practices, and regulatory compliance (GDPR, CCPA).
• Experience with enterprise data platforms, cloud technologies, and data integration tools.
• Proven ability to influence senior stakeholders and drive cross-functional alignment.
• Excellent communication and leadership skills with a track record of building high-performing teams.
• Demonstrated ability to build and scale data & analytics organizations or practices.
• Experience implementing enterprise data governance processes (privacy, MDM, access rights, data integrity).
• Experience procuring and integrating third-party data sources.
Preferred Skills
• Experience with BI and analytics tools such as Power BI, Tableau, or Looker.
• Familiarity with distributed data strategies and modern cloud storage technologies.
• Strong written and verbal communication skills with the ability to simplify complex concepts.
• Proven ability to build performance metrics for analytics models and digital properties.
Who You'll Work With
Reports to: Executive Director
Works closely with: Technology, Analytics, Product, Finance, and Business Unit leadership teams
• Part of a team that values collaboration, communication, and doing what's right for the guest
Responsibilities:
Enterprise Data Strategy & Roadmap
  • Define a multi-year data strategy aligned to enterprise goals; establish the portfolio, prioritization model, and investment thesis for data initiatives.
  • Create a scalable data operating model (centralized/Hub-and-Spoke/Federated) with clear ownership (RACI), standards, and funding approach.

Data Governance & Risk
  • Operationalize governance (policies, standards, controls) across privacy, security, lineage, quality, retention, and AI risk.
  • Implement data stewardship and issue management with measurable defect reduction and remediation SLAs.

Data Products & Enablement
  • Lead the definition and lifecycle of high-value data products.
  • Partner with analytics/engineering to define product requirements, success metrics, and adoption plans.
  • Drive data literacy programs and self-service adoption for business stakeholders.

Value Realization & Portfolio Management
  • Build business cases and track ROI on data investments; establish value frameworks (revenue uplift, cost avoidance, risk reduction, cycle-time).
  • Run quarterly portfolio reviews with Finance and BU leaders; rebalance based on outcomes.

Architecture Alignment & Platform Strategy
  • Partner with Enterprise Data on platform roadmaps (data lakehouse/warehouse, MDM, catalog, governance tools, semantic layers, AI/ML platforms).
  • Promote standardized data models and interoperability across domains (e.g., finance, customer, product, operations, HR).

AI/Advanced Analytics Readiness
  • Establish responsible AI guardrails and data readiness for ML/GenAI use cases (access controls, PII handling, provenance, monitoring).
  • Prioritize and incubate analytics/AI use cases with clear problem statements and success criteria.

Change Leadership & Communications
  • Lead exec-level updates, socialize strategy, and align incentives with BU leaders.
  • Develop communication plans for policy changes, new capabilities, and enablement milestones.

Qualifications:
All qualified applicants will receive consideration for employment with RaceTrac without regard to their race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.

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