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Texas State Technical College

Public technical college serving Texas

Data & Analytics Engineer

Data Engineering +1Confirmed live in the last 24 hours
Full-timeTexas, USANo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Science, Data Science, Information Systems, Statistics, Mathematics, Engineering, or a related field is required; relevant experience may be considered in lieu of formal education where appropriate.
  • Three to five years of experience in data analytics, analytics engineering, business intelligence, data science, data engineering, or a related field is required.
  • Experience with Microsoft Power BI or comparable business intelligence and visualization technologies, developing analytical data models, and transforming source data into analytics-ready datasets is required.
  • Experience working with data warehouses, lakehouses, data pipelines, or modern cloud-based data platforms, and software development practices such as source control, testing, documentation, and code review is required.
  • Understanding of data visualization, dimensional modeling, business intelligence concepts, statistical analysis, and data science concepts is required.
  • Proficiency in Python or a comparable programming language used for data analysis, automation, or data science is required.
  • Strong SQL skills and experience working with complex analytical datasets are required.
  • Ability to translate business requirements and questions into data and analytical solutions is required.
  • Ability to design, develop, and maintain data and analytics solutions using Microsoft Fabric, SQL, Python, and related technologies, applying data modeling, software engineering, version control, testing, documentation, and deployment practices.
  • Ability to develop Power BI dashboards, semantic models, and analytical products using DAX, Power Query, and Microsoft Fabric.
  • Ability to apply data science, statistical modeling, machine learning, and predictive analytics techniques to institutional challenges, and to learn and apply emerging data, analytics, artificial intelligence, and cloud technologies.
  • Ability to translate complex business requirements into scalable, reliable, and well-documented data and analytics solutions.
  • Ability to apply data governance, data quality, privacy, security, and responsible artificial intelligence practices to ensure trustworthy and compliant analytical solutions.
  • Ability to communicate analytical findings and technical concepts clearly to technical and non-technical audiences.
  • Ability to manage multiple assignments and priorities while maintaining accuracy and quality, and to contribute to shared development practices, standards, code reviews, and continuous improvement.
  • Ability to collaborate across Data Engineering, Data Governance, Institutional Research, Application Engineering, and business stakeholder teams.
  • Strong analytical, problem-solving, critical-thinking, written, and verbal communication skills.
  • Must be reachable during assigned work hours through established communication channels.
  • Must complete federal Employment Eligibility Verification Form I-9 and present acceptable original documents proving identity and authorization to work in the United States no later than the third day of employment.
  • A criminal history background check is required for finalists.

Responsibilities

  • Demonstrate the institution’s core values of excellence, accountability, service, and integrity with internal and external stakeholders, customers, students, and community members.
  • Design, develop, and maintain scalable data and analytics solutions using Microsoft Fabric, SQL, Python, and related technologies.
  • Transform raw and complex source data into well-structured, analytics-ready datasets for institutional reporting, business intelligence, advanced analytics, and data science initiatives.
  • Develop and maintain analytical data models, data transformations, automated pipelines, notebooks, and reusable data assets, partnering with Data Engineering to manage Silver and Gold architectural layers.
  • Apply software and data engineering practices, including version control, testing, technical documentation, code reviews, and deployment management; troubleshoot and optimize solutions for performance, reliability, and maintainability.
  • Design and deliver enterprise Power BI dashboards, reports, semantic models, and analytical tools for institutional decision-making.
  • Build and maintain reusable semantic models, standardized measures, and institutional performance metrics using Power BI, DAX, Power Query, and Microsoft Fabric.
  • Apply data visualization, dimensional modeling, performance tuning, row-level security, and report lifecycle management practices.
  • Partner with Data Governance and Institutional Research to ensure calculations, metrics, and institutional data definitions are consistently implemented across analytical deliverables; support and mentor team members in using shared analytical assets.
  • Serve as a technical resource for data science, predictive analytics, statistical modeling, and machine learning across the institution.
  • Evaluate complex business problems to determine where advanced statistical or machine-learning methods can provide value beyond traditional reporting.
  • Design, develop, validate, and operationalize predictive and analytical models for institutional priorities, including enrollment forecasting, student retention and completion, program alignment, financial optimization, and operational capacity planning.
  • Perform feature engineering, exploratory data analysis, regression, classification, clustering, and time-series forecasting; collaborate with Data Engineering and Application Engineering to integrate model outputs into enterprise platforms and workflows.
  • Evaluate and prototype analytics, machine-learning, and generative artificial-intelligence capabilities to address institutional challenges and improve operational effectiveness.
  • Ensure data and analytics solutions comply with institutional data governance, security, privacy, and data-handling standards.
  • Collaborate with Data Governance on data quality, lineage, metadata dictionaries, data classification, and responsible data usage.
  • Apply responsible artificial-intelligence and data-science principles, ensuring transparency, explainability, reproducibility, appropriate oversight, and comprehensive documentation of data sources, transformations, calculations, and analytical methods.
  • Engage institutional stakeholders to translate operational needs into data and analytics solutions.
  • Partner across Data Engineering, Data Governance, Institutional Research, Application Engineering, and academic and administrative units to deliver integrated data products.
  • Communicate analytical findings, methodology, and technical concepts to technical and non-technical audiences.
  • Participate in technical design reviews, peer code reviews, and standard-setting initiatives; monitor advances in Microsoft Fabric, Power BI, and artificial-intelligence technologies to drive continuous improvement.
  • Lead communication efforts for projects, programs, or teams, facilitating clear alignment and transparency; represent the team or function in cross-functional settings.
  • Take ownership of assigned responsibilities, deliver results, proactively address challenges, and identify improvements while adapting to changing priorities.
  • Collaborate with colleagues, support shared goals, and contribute to responsive service and a positive team dynamic.
  • Translate goals and priorities into actionable plans, manage time, resources, and dependencies, and adjust plans to maintain quality and timeliness.
  • Apply independent judgment and data-driven critical thinking to evaluate options, balance risks, make decisions, solve problems, and improve processes.
  • Lead by example, provide direction and support to team members, and offer coaching, feedback, and mentorship to foster professional growth.
  • Perform work primarily in an office or academic environment, with possible movement across campus and participation in meetings with faculty, staff, and students.
  • Travel periodically within Texas to campuses or meetings beyond the designated or nearest base campus as business needs require.
  • Handle confidential and sensitive information appropriate to assigned responsibilities; perform additional duties as assigned.

Desired Qualifications

  • A master's degree in Computer Science, Data Science, Information Systems, Statistics, Mathematics, Engineering, or a related field is preferred.
  • Five or more years of experience in data analytics, analytics engineering, business intelligence, data science, data engineering, or a related field is preferred.
  • Experience with Microsoft Fabric, including OneLake, Lakehouse, Warehouse, Data Factory, notebooks, pipelines, or semantic models.
  • Experience with Power BI, including semantic modeling, DAX, Power Query, performance optimization, and deployment practices.
  • Experience with Azure data and analytics services.
  • Experience developing predictive models or machine-learning solutions.
  • Knowledge of statistical modeling, forecasting, regression, classification, clustering, and other advanced analytical techniques.
  • Experience with machine-learning frameworks such as scikit-learn, TensorFlow, PyTorch, or similar technologies.
  • Understanding of MLOps concepts, including model versioning, deployment, monitoring, and lifecycle management.
  • Experience with Microsoft Purview or similar data governance and lineage technologies.
  • Experience with CI/CD or DevOps practices for data and analytics solutions.
  • Experience with higher education, student, financial, workforce, or other complex institutional data.
  • Knowledge of data privacy, security, and regulatory requirements such as FERPA.

About the Company

Texas State Technical College

Public technical college serving Texas

Texas State Technical College is a public two-year institution that prepares students for technical careers across Texas. It offers certificates and associate degrees in fields such as aviation, health care, information technology, manufacturing and skilled trades. Students learn through campus laboratories, hands-on instruction and flexible formats that include online programs, dual credit and continuing education. The college also works with employers on workforce training and helps students connect their education with job opportunities through career services and industry relationships. Founded in 1965, Texas State Technical College is headquartered in Waco, Texas.

Company size
Not listed
Company stage
Not listed
Total funding
Not listed
Headquarters
Waco, TX
Founded
1965

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