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Technology Operations Enterprise Data Strategy Jobs in Georgia

RaceTrac

Director of Data Strategy

Atlanta, GA

This leader ensures that data becomes a strategic asset--fueling revenue growth, operational ... Experience with enterprise data platforms, cloud technologies, and data integration tools. * Proven ...

Sarian, Inc.

Enterprise Data Architect

Atlanta, GA · On-site

Partner with Key Roles (Business and Technology) to shape the Enterprise Data & Analytics strategy, provide hands on guidance to convert the strategy to architecture/Solutions that are aligned to ...

TIER4 GROUP

Data Architect

Atlanta, GA · Hybrid

$61.25 - $78.75/hr

... with our technology strategy. In this role, you will guide the design of a scalable data ... current operations and future innovation. Your work will be key to supporting our digital ...

Palnar

Snowflake Data Architect

Alpharetta, GA · On-site

$62.25 - $80/hr

The strategy includes data model designs, database development standards, implementation and ... Planning and execution of big data solutions using technologies such as Snowflake/Synapse/MongoDB.

Trella Health

Vice President, Data Strategy

Atlanta, GA · On-site

... operational, and financial outcomes. The ideal candidate is equal parts strategist, technologist ... Define and execute a multi-year data and AI roadmap aligned to our enterprise strategy with clear ...

Trella Health

... operational, and financial outcomes. The ideal candidate is equal parts strategist, technologist ... Define and execute a multi-year data and AI roadmap aligned to our enterprise strategy with clear ...

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Technology Operations Enterprise Data Strategy information

What are the key skills and qualifications needed to thrive in Technology Operations Enterprise Data Strategy, and why are they important?

To excel in Technology Operations Enterprise Data Strategy, you need strong expertise in data management, analytics, and strategic planning, often backed by a degree in computer science, information systems, or a related field. Familiarity with data warehousing solutions, ETL tools, data governance frameworks, and certifications like CDMP or AWS Certified Data Analytics is highly valuable. Exceptional problem-solving, stakeholder management, and communication skills help drive cross-functional initiatives and align data strategies with business goals. These competencies ensure effective data-driven decision making, operational efficiency, and long-term organizational success.

How does a Technology Operations Enterprise Data Strategy professional typically collaborate with other departments within an organization?

Professionals in Technology Operations Enterprise Data Strategy work closely with multiple departments, such as IT, business analytics, compliance, and executive leadership. They often facilitate communication between technical teams and business stakeholders to ensure that data initiatives align with organizational goals. This role involves coordinating data governance policies, integrating new technologies, and supporting data-driven decision-making across the enterprise. Successful collaboration requires strong communication skills and a deep understanding of both technical and business perspectives.

What is Technology Operations Enterprise Data Strategy?

Technology Operations Enterprise Data Strategy refers to the planning, management, and implementation of data-related processes and technologies across an organization to support its operational goals. This role involves setting standards for data governance, ensuring data quality, and aligning data initiatives with business objectives. Professionals in this field work to optimize data flow, storage, and security, enabling better decision-making and efficiency. They often collaborate with IT, business units, and data analytics teams to ensure data assets are leveraged effectively across the enterprise.

What is the difference between Technology Operations Enterprise Data Strategy vs Data Analyst?

AspectTechnology Operations Enterprise Data StrategyData Analyst
CredentialsTypically requires a degree in IT, Data Science, or related fields; certifications like CDMP or CBIP are commonRequires a degree in Statistics, Data Science, or related fields; certifications like Microsoft Data Analyst Associate or Tableau Desktop Specialist are common
Work EnvironmentFocuses on strategic planning, data governance, and infrastructure within enterprise IT teamsFocuses on data collection, analysis, and reporting to support business decisions
Employer & Industry UsageUsed in large organizations managing enterprise data assets and IT operationsUsed across industries for data reporting, visualization, and insights

While Technology Operations Enterprise Data Strategy professionals focus on aligning data initiatives with business goals and managing data infrastructure, Data Analysts primarily analyze data to generate actionable insights. Both roles require strong analytical skills but differ in scope and strategic involvement.

What cities in Georgia are hiring for Technology Operations Enterprise Data Strategy jobs? Cities in Georgia with the most Technology Operations Enterprise Data Strategy job openings:
Technology Operations Enterprise Data Strategy jobs near you

Director of Data Strategy

RaceTrac

Atlanta, GA

Full-time

Re-posted 11 days ago

RaceTrac rating

4.8

Company rating: 4.8 out of 10

Based on 196 frontline employees who took The Breakroom Quiz

36th of 46 rated convenience stores

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

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