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How much do data core systems jobs pay per year?

As of Jun 24, 2026, the average yearly pay for data core systems in the United States is $111,995.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is the difference between Data Core Systems vs Data Analyst?

AspectData Core SystemsData Analyst
Required CredentialsBachelor's in Computer Science, Data Management certificationsBachelor's in Statistics, Data Analysis certifications
Work EnvironmentIT departments, data infrastructure teamsBusiness units, analytics teams
Employer & Industry UsageTech companies, data-driven organizationsFinance, marketing, healthcare sectors

Data Core Systems professionals focus on managing and maintaining data infrastructure, ensuring data integrity and system performance. Data Analysts interpret data to generate insights and support decision-making. While both roles work with data, Data Core Systems specialists handle the technical backend, whereas Data Analysts focus on analysis and reporting.

What are Data Core Systems?

Data Core Systems refer to the foundational software and hardware infrastructure responsible for managing, storing, and processing large volumes of data within an organization. These systems ensure data is accessible, secure, and efficiently handled for various business operations and analytics. They often include databases, data warehouses, storage solutions, and data management tools, forming the backbone of enterprise data operations. Data Core Systems play a crucial role in enabling data-driven decision-making and supporting digital transformation initiatives.

What are some common challenges faced by professionals working in Data Core Systems roles, and how are they typically addressed?

Professionals in Data Core Systems often encounter challenges such as ensuring data integrity across complex, large-scale databases and coordinating with multiple teams to implement system updates without disrupting ongoing operations. Addressing these challenges usually involves robust change management processes, regular system audits, and close collaboration with software engineers, database administrators, and security teams. Staying current with evolving database technologies and adopting automated monitoring tools also help maintain optimal system performance and reliability. Open communication and thorough documentation are key practices for minimizing errors and streamlining troubleshooting.

What are the key skills and qualifications needed to thrive as a Data Core Systems Specialist, and why are they important?

To thrive as a Data Core Systems Specialist, you need strong expertise in database management, data architecture, and systems integration, typically supported by a degree in computer science or a related field. Familiarity with SQL, cloud platforms (like AWS or Azure), and data warehousing tools, along with relevant certifications (such as AWS Certified Data Analytics or Microsoft Certified: Azure Data Engineer), is often required. Analytical thinking, problem-solving, and effective communication are vital soft skills for collaborating with cross-functional teams and addressing complex data challenges. These competencies are crucial for ensuring the reliability, scalability, and security of organizational data infrastructure.
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Data Core Systems jobs near you
Infographic showing various Data Core Systems job openings in the United States as of June 2026, with employment types broken down into 87% Full Time, 11% Part Time, and 2% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $111,995 per year, or $53.8 per hour.
SAP Datasphere, SAC, and AI Architect

SAP Datasphere, SAC, and AI Architect

Data-Core Systems

Middletown, PA • On-site

$79.25 - $106.75/hr

Other

Posted yesterday

Job description

Data-Core Systems, Inc. is a provider of information technology, consulting, and business process services. We offer breakthrough tech solutions and have worked with companies, hospitals, universities, and government organizations. A proven partner with a passion for client satisfaction, we combine technology innovation, business process expertise, and a global, collaborative workforce that exemplifies the future of work. For more information about Data-Core Systems, Inc., please visit https://datacoresystems.com/.
Our client is a roadway system, and as a part of their digital transformation, they are implementing a solution based on SAP BRIM & Microsoft Dynamics CE.
Data-Core Systems Inc. is seeking a SAP Datasphere, SAC, and AI Architect to be a part of our Consulting team. You will participate and effectively contribute to the design, development, and implementation of complex applications, often using new technologies. You will provide technical expertise and systems design for individual initiatives. You will have the opportunity to work with other SME consultants from our existing team.
Roles & Responsibilities:
Enterprise Data & Analytics Architecture.

  • Lead the architecture and design of enterprise data, analytics, and AI solutions leveraging SAP Datasphere, SAP Analytics Cloud (SAC), and SAP BTP.
  • Define data architecture standards, governance models, integration strategies, and best practices.
  • Design scalable and secure enterprise data models supporting reporting, analytics, planning, forecasting, and AI use cases.
  • Develop architecture roadmaps aligned with organizational digital transformation strategies.
SAP Datasphere Architecture & Engineering.
  • Design and implement SAP Datasphere solutions for enterprise data integration, virtualization, modeling, and governance.
  • Architect data pipelines integrating SAP and non-SAP source systems.
  • Define semantic models, business layers, and data products for analytics consumption.
  • Optimize data performance, scalability, and security within Datasphere environments.
  • Establish data governance, lineage, cataloging, and quality management practices.
SAP Analytics Cloud (SAC) Architecture.
  • Design enterprise reporting, dashboarding, and planning solutions using SAP Analytics Cloud.
  • Architect SAC models, stories, planning applications, and predictive analytics solutions.
  • Define KPI frameworks, executive dashboards, and operational reporting standards.
  • Support integration between SAC, Datasphere, SAP S/4HANA, BW/4HANA, and third-party data sources.
  • Optimize SAC performance, security roles, and user experience.
AI & Intelligent Enterprise Solutions.
  • Lead the architecture and integration of AI/ML capabilities within SAP environments.
  • Evaluate and implement SAP AI technologies, including:
    • SAP AI Core.
    • SAP AI Launchpad.
    • Joule and Generative AI capabilities.
    • Predictive analytics and machine learning models.
  • Design AI-enabled use cases, including:
    • Forecasting.
    • Intelligent automation.
    • Predictive maintenance.
    • Customer analytics.
    • Financial insights.
  • Collaborate with data science teams to operationalize AI/ML models within enterprise workflows.
Integration & Technical Leadership.
  • Architect integrations across:
    • SAP S/4HANA.
    • SAP BW/4HANA.
    • SAP BTP.
    • SAP SuccessFactors.
    • SAP Ariba.
    • External cloud platforms and data lakes.
  • Guide development teams on APIs, data services, event processing, and cloud-native integration patterns.
  • Ensure enterprise security, compliance, and performance standards are met.
Governance, Security & Compliance.
  • Establish enterprise standards for:
    • Data governance.
    • Data quality.
    • Master data management.
    • Security and access controls.
    • AI governance and responsible AI practices.
  • Ensure compliance with organizational and regulatory requirements.
Project Leadership & Stakeholder Engagement.
  • Lead architecture workshops, solution reviews, and technical strategy sessions.
  • Collaborate with business stakeholders to translate business requirements into scalable analytics and AI solutions.
  • Provide technical leadership and mentoring to developers, analysts, and engineering teams.
  • Communicate architecture decisions, risks, and recommendations to executive leadership.
Documentation & Operational Support.
  • Develop and maintain architecture diagrams, standards, technical specifications, and operational procedures.
  • Support testing, deployment, cutover, and post-production stabilization activities.
  • Assist with production issue resolution and continuous improvement initiatives.
Required Skills & Experience:
  • 8+ years of enterprise SAP data and analytics experience.
  • 5+ years of hands-on experience with SAP Datasphere and/or SAP Analytics Cloud.
  • Proven experience in architecting enterprise analytics and reporting platforms.
  • Experience implementing AI/ML or predictive analytics solutions in enterprise environments.
  • Proven experience, expertise, and strong understanding in:
    • SAP Datasphere.
    • SAP Analytics Cloud (SAC).
    • SAP Business Technology Platform (BTP).
    • Data modeling and enterprise analytics architecture.
    • Data warehousing concepts.
    • ETL/ELT processes.
    • Cloud-native architectures.
    • Data governance and security.
    • AI/ML lifecycle management.
    • Python or related analytics/programming languages.
    • APIs and integration services.
    • Data visualization and dashboard design.
  • SAP BW/4HANA, SAP HANA native modeling, SAP AI Core, and AI Launchpad, Generative AI integrations, and large-scale cloud data platforms.
  • Experience in utilities, telecommunications, finance, manufacturing, or public sector industries.
  • Experience with Agile, DevOps, and CI/CD delivery methodologies.
Certifications & Education Qualifications:
  • Preferred certifications include one or more of the following:
    • SAP Certified Application Associate - SAP Analytics Cloud.
    • SAP Certified Technology Specialist - SAP Datasphere.
    • SAP Certified Development Associate - SAP Extension Suite / SAP BTP.
    • SAP Certified Application Associate - SAP BW/4HANA.
    • Cloud certifications (AWS, Azure, Google Cloud).
    • AI/ML certifications from SAP, Microsoft, AWS, or Google preferred.
  • Bachelor's degree in Computer Science, Information Systems, Engineering, Business Technology, or a related technical discipline.
  • An equivalent combination of education and relevant experience may be considered.

We are an equal opportunity employer.
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