Data Engineer

SJSU Research Foundation • San Jose, CA

3d • $77,000 - $85,000

About The Position

The Data Engineer supports SJSU's Campus Data Warehousing and Business Intelligence initiatives through the development, integration, and maintenance of enterprise data solutions. The position contributes to the development and maintenance of data pipelines and data models that integrate information from multiple university systems into trusted, governed data platforms used for institutional reporting, analytics, and data-driven decision-making.

Working under the guidance of senior technical staff, the Data Engineer applies knowledge of computer science, information systems, database technologies, programming, data architecture, and cloud-based data platforms to develop and support enterprise data solutions. The position works with technical teams and university stakeholders to analyze requirements, troubleshoot data and system issues, design technical solutions, document business and technical requirements, and support vendor and locally developed systems.

Requirements

• Bachelor's degree or equivalent in Computer Science, Computer Engineering, Information Systems, Data Science, Software Engineering, or a closely related technical or quantitative field that includes coursework in programming, databases, data structures, systems analysis, statistics, or comparable computing disciplines.
• 1 + year of professional experience in data engineering, database development, software development, data integration, data analytics development, business applications, or a closely related technical field.
• Experience through professional employment or internships applying programming, database, data integration, and/or data analytics principles to information systems.
• Experience using SQL and programming or scripting languages such as Python or Java.
• Experience with relational databases or data platforms such as Oracle, Snowflake, or Databricks.
• Experience with cloud platforms such as AWS or Google Cloud Platform.
• Professional knowledge of programming, database systems, data structures, data integration, and data engineering concepts.
• Working knowledge of relational database concepts and SQL, including the ability to develop and troubleshoot database queries.
• Knowledge of programming or scripting such as Python, Java, JavaScript, bash script, cron syntax, or similar technologies.
• Working knowledge of data pipeline development, data transformation, ETL/ELT, metadata, and data warehousing concepts.
• Knowledge of cloud computing and modern data platforms such as AWS, Google Cloud Platform, Databricks, Snowflake, Apache AIrflow, or comparable technologies.
• Ability to analyze SQL, source data, application logic, system logs, and code to identify and troubleshoot technical issues.
• Ability to work with data from multiple source systems and apply technical requirements and business rules to data solutions.
• Knowledge of software and systems development lifecycle methodologies, including Agile and Waterfall.
• Working knowledge of application development, testing, deployment, monitoring, and production-support practices.
• Knowledge of analytical concepts including statistical analysis, data mining, forecasting, regression, and predictive modeling.
• Ability to analyze structured and unstructured datasets using appropriate technical and analytical methods.
• Ability to prepare and maintain technical documentation, including data mappings, requirements, integration logic, and operational procedures.
• Ability to communicate technical information and collaborate effectively with technical staff and university stakeholders.
• Ability to analyze technical problems, identify potential solutions, and escalate or collaborate on complex issues as appropriate.
• Ability to learn and apply emerging technologies related to data engineering, analytics, databases, and cloud computing.
• Strong analytical curiosity and comfort working with structured and unstructured datasets.
• Periodic contact with employees at all levels, San Jose State University faculty and staff, and/or vendors, with the ability to discuss and appropriately respond to inquiries and requests.
• Strength, dexterity, and coordination and/or ability to use a computer keyboard and read a video display terminal on a regular basis.
• Able to lift, relocate, and integrate IT and lab-related equipment.
• Ability to listen to verbal requests from customers, clients, and vendors, and to respond appropriately.

Nice To Haves

• Master’s in Computer Science (Software Engineering), Business Administration, or closely related technical or quantitative field.
• Experience developing and maintaining ETL/ELT processes and micro-batch data pipelines.
• Experience with visualization and analytics platforms such as Tableau, Looker, AWS QUICK, or comparable technologies.
• Exposure to agentic AI, speech-to-text, and Retrieval-Augmented Generation (RAG) technologies.
• Some experience or coursework in data mining, forecasting, deep learning, machine learning, or predictive modeling is a plus

Responsibilities

• Develop, test, implement, and maintain data pipelines and integration processes that extract, transform, and load data from multiple enterprise source systems into SJSU's data warehouse and analytics platforms.
• Develop and maintain SQL queries, database objects, data transformations, and data models in support of reporting and analytics requirements.
• Apply programming and scripting languages such as Python, Java, SQL, or similar technologies to develop, maintain, and support data solutions.
• Analyze source-system data structures, relationships, and business rules to support integration into enterprise data platforms.
• Troubleshoot data pipeline, integration, database, and production data issues by reviewing SQL queries, source data, system logs, application logic, and code; collaborate with senior developers and other technical teams to resolve more complex issues.
• Develop and maintain processes to validate data quality, integrity, consistency, and completeness.
• Develop and deploy scalable, secure, and reliable data solutions in cloud environments to support analytics and business operations.
• Support data solutions using relational databases, cloud computing environments, data lakehouse technologies, and platforms such as Oracle, Snowflake, Databricks, AWS, and Google Cloud Platform.
• Apply established data architecture, ETL/ELT, data warehousing, metadata management, and database design principles when developing and maintaining data solutions.
• Collaborate with data engineers, analysts, application developers, system administrators, and functional stakeholders to translate business requirements into technical data requirements and solutions.
• Support analytical methodologies including segmentation, statistical analysis, regression, forecasting, data mining, and predictive modeling as appropriate.
• Provide production support for applications and data solutions, ensuring SLA compliance through effective monitoring, troubleshooting, incident resolution, testing, deployment, and ongoing maintenance.
• Analyze structured and unstructured datasets to identify trends, anomalies, relationships, and information useful for university decision-making.
• Support the team in building trusted relationships with internal and external stakeholders through reliable, accurate data work.
• Follow IT policies and standards for maintaining consistency across SJSU campus.
• Stay current on technology trends and proactively share learnings with the team.

Benefits

• Four company health insurance plans to choose from (employee contributions differ according to plan and level of coverage).
• Employer-paid dental and vision for both employee and eligible dependents.
• Life, AD&D, LTD with supplemental coverage opportunities.
• 14 paid federal & state holidays.
• Retirement Plan: 403 (b) employee contribution plan component and a 403 (b) employer contribution component, which vests immediately.
• Vacation-hour accruals and separate sick-hour accumulations.
• Employee discounts.
• Paid training and professional-development conferences.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level