Data & Analytics Engineer

The Data & Analytics Engineer provides hands-on development of data, analytics, business intelligence, and data science solutions to support institutional decision-making and day-to-day operations. The role partners across the analytics lifecycle using Microsoft Fabric and Power BI, and applies advanced analytics and AI expertise when needed.

Responsibilities

• Designs, develops, and maintains scalable data and analytics solutions using Microsoft Fabric, SQL, Python, and related technologies.
• Transforms raw and complex source data into analytics-ready datasets to support institutional reporting, business intelligence, advanced analytics, and data science initiatives.
• Develops and maintains analytical data models, data transformations, automated pipelines, notebooks, and reusable data assets, coordinating with Data Engineering to manage Silver and Gold architectural layers.
• Applies software and data engineering practices including version control, testing, technical documentation, code reviews, and deployment management while troubleshooting and optimizing for performance, reliability, and maintainability.
• Designs and delivers enterprise Power BI dashboards, reports, semantic models, and analytical tools that support institutional decision-making.
• Builds and maintains reusable semantic models, standardized measures, and institutional performance metrics using Power BI, DAX, Power Query, and Microsoft Fabric.
• Implements best practices for data visualization, dimensional modeling, performance tuning, row-level security, and report lifecycle management.
• Partners with Data Governance and Institutional Research to ensure calculations, metrics, and institutional data definitions are consistently implemented across analytical deliverables and supports mentoring team members in using shared analytical assets.
• Serves as a key technical resource for data science, predictive analytics, statistical modeling, and machine learning across the institution.
• Evaluates complex business problems to identify where advanced statistical or machine-learning methods provide actionable value beyond traditional reporting.
• Designs, develops, validates, and operationalizes predictive and analytical models aligned to institutional priorities including enrollment forecasting, student retention and completion, program alignment, financial optimization, and operational capacity planning.
• Executes feature engineering, exploratory data analysis, regression, classification, clustering, and time-series forecasting, coordinating with Data Engineering and Application Engineering to integrate model outputs into enterprise platforms and workflows.
• Evaluates and prototypes emerging capabilities in analytics, machine learning, and generative artificial intelligence to address institutional challenges and improve operational effectiveness.
• Ensures data and analytics solutions comply with institutional data governance, security, privacy, and data-handling standards.
• Collaborates with Data Governance to support data quality, lineage, metadata dictionaries, data classification, and responsible data usage.
• Embeds responsible AI and data science principles across deliverables, including transparency, explainability, reproducibility, appropriate oversight, and documentation of data sources, transformations, calculations, and methodologies.
• Engages with institutional stakeholders to convert complex operational needs into robust data and analytics solutions.
• Partners across Data Engineering, Data Governance, Institutional Research, Application Engineering, and academic and administrative units to deliver integrated data products.
• Communicates analytical findings, methodology, and technical concepts to technical and non-technical audiences.
• Participates in technical design reviews, peer code reviews, and standard-setting initiatives, while monitoring developments in Microsoft Fabric, Power BI, and AI technologies.
• Leads communications for projects, programs, or teams to maintain clarity, alignment, and transparency.
• Demonstrates advanced mastery of required technical and functional competencies and takes ownership for delivering expected results.
• Collaborates respectfully with colleagues, contributing to community and partnership, and translates priorities into actionable plans while managing time, resources, and dependencies.
• Provides clear direction, support, and inspiration to team members while aligning work with organizational goals.

Requirements

• Bachelor’s degree in Computer Science, Data Science, Information Systems, Statistics, Mathematics, Engineering, or a related field.
• 3 to 5 years of experience in data analytics, analytics engineering, business intelligence, data science, data engineering, or a related field.
• Experience with Microsoft Power BI (or comparable BI technologies), including developing analytical data models and transforming source data into analytics-ready datasets.
• Experience with data warehouses, lakehouses, data pipelines, or modern cloud-based data platforms with software development practices such as source control, testing, documentation, and code review.
• Understanding of data visualization, dimensional modeling, business intelligence concepts, statistical analysis, and data science concepts.
• Proficiency in Python (or a comparable programming language) used for data analysis, automation, or data science.
• Strong SQL skills and experience working with complex analytical datasets.
• Ability to translate business requirements and questions into data and analytical solutions.

Technologies

• Microsoft Fabric, Power BI, SQL, Python, DAX, Power Query
• OneLake, Lakehouse, Warehouse, Data Factory
• Notebooks, pipelines, semantic models
• Azure, scikit-learn, TensorFlow, PyTorch
• Microsoft Purview
• FERPA, CI/CD, DevOps, MLOps
• Generative artificial intelligence

Preferred Qualifications

• Master’s degree in Computer Science, Data Science, Information Systems, Statistics, Mathematics, Engineering, or a related field.
• 5+ years of experience in data analytics, analytics engineering, business intelligence, data science, data engineering, or a related field.
• 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 and forecasting, including 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 working with higher education, student, financial, workforce, or other complex institutional data.
• Knowledge of data privacy, security, and regulatory requirements such as FERPA.
• Relevant experience may be considered in lieu of formal education where appropriate, consistent with TSTC’s equivalency philosophy.

Skills & Abilities

• Designs, develops, and maintains data and analytics solutions using Microsoft Fabric, SQL, Python, and related technologies, including data modeling, software engineering practices, and deployment management.
• Develops Power BI dashboards, semantic models, and analytical products using DAX, Power Query, and Microsoft Fabric.
• Applies data science, statistical modeling, machine learning, and predictive analytics to address institutional challenges and adapts to emerging tools and technologies.
• Translates complex business requirements into scalable, reliable, and well-documented data and analytics solutions.
• Applies data governance, data quality, privacy, security, and responsible AI practices to support trustworthy and compliant analytical solutions.
• Communicates analytical findings and technical concepts clearly to technical and non-technical audiences.
• Manages multiple assignments and priorities while maintaining accuracy, quality, and attention to detail, contributing to shared development practices, standards, code reviews, and continuous improvement.
• Collaborates effectively across Data Engineering, Data Governance, Institutional Research, Application Engineering, and business stakeholder teams.
• Demonstrates strong analytical, problem-solving, critical-thinking, and written and verbal communication skills.

Core Competencies

• Communication: Leads communication efforts for projects, programs, or teams to ensure clarity, alignment, and transparency.
• Job Knowledge & Job Performance: Demonstrates advanced knowledge and mastery of the technical and functional competencies required for the role.
• Ownership & Accountability: Takes full ownership of assigned responsibilities and is accountable for delivering results that meet or exceed expectations.
• Teamwork & Service: Collaborates effectively and respectfully with colleagues, welcoming different perspectives and fostering community and partnership.
• Planning & Execution: Translates goals and priorities into actionable plans, managing time, resources, and dependencies to deliver results.
• Critical Thinking & Judgement: Exercises independent judgment and applies critical thinking to evaluate options, balance risks, and make decisions that support both team and organizational success.
• Leadership Without Authority: Leads by example, acting as a visible role model of the organization’s values, integrity, and high standards.

Employment Classification

This position is classified under the Fair Labor Standards Act (FLSA) as exempt and operates in a professional and instructional environment that may include campus offices, classrooms, or lab settings.

Reasonable Accommodations

TSTC will provide reasonable accommodations to qualified individuals with disabilities to enable them to perform the essential functions of the position.

Work Environment

• The role may require movement across campus, participation in meetings, and engagement with faculty, staff, and students to support institutional goals.
• Work is primarily performed in an office or academic environment using standard technology and communication tools.

Telework Eligibility

This position may be considered for telework options based on eligibility under TSTC’s Telework Policy, aligned with State of Texas requirements.

Availability and Communication Expectations

The employee must be reachable during assigned work hours through established communication channels as required by the role.

Travel Requirements

Periodic in-state travel to campuses or meetings beyond the employee’s designated or nearest base campus may be required based on business needs and will comply with TSTC and State of Texas requirements.

Confidentiality and Sensitive Information

This role requires attention to confidential and sensitive information appropriate to assigned responsibilities.

Employment Eligibility Verification

• If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form.
• You will be required to present acceptable and original documents to prove identity and authorization to work in the United States.
• Documents need to be presented no later than the third day of employment.
• Failure to do so will result in loss of employment at TSTC.

Background Checks

A criminal history background check will be required for the finalist(s) under consideration for this position.

Location

Texas (onsite)

Minimum Experience and Education

• Minimum experience: 3 years
• Education: Bachelor’s degree