Data Warehouse Administrator I/II

Santa Clara Valley Transportation Authority • San Jose, CA

4d • Onsite

About The Position

Are you passionate about transforming data into meaningful insights that help organizations make better decisions? Join our team as a Data Warehouse Administrator I and help build, support, and improve enterprise data solutions that power reporting, analytics, and operational decision-making across VTA. In this role, you will contribute to the development and support of data pipelines, ETL/ELT processes, data integrations, and analytical solutions that bring together information from multiple enterprise systems. You will work with SQL, programming languages, modern data tools, and reporting platforms while helping ensure data accuracy, reliability, and quality. You will collaborate with experienced data engineers, technology teams, and business stakeholders to understand data needs, troubleshoot issues, document solutions, and deliver reliable data products that support reporting, automation, and analytics. Whether you are starting your career in data engineering or looking to grow your skills in enterprise data platforms, this is an opportunity to work with modern database technologies, cloud data solutions, APIs, automation tools, and analytics platforms while contributing to initiatives that have a meaningful impact on public transportation and the community we serve. The Technology Department strives to provide the highest quality technology-based services and solutions, in the most cost-effective manner, to facilitate the needs of our customers within VTA and the customers VTA serves. Under general supervision, the Data Warehouse Administrator I builds and maintains data processing systems and pipelines that combine core data sources into accessible structures to support reporting and analytical systems. This is the entry and first working level of the Data Warehouse Administrator series. This class performs work of routine and average difficulty. Incumbents will initially perform tasks under close supervision. Tasks performed by the Data Warehouse Administrator I will be in a learning capacity. As knowledge and skill increases, the incumbent will perform work more independently. Incumbents at this level are involved with developing, coding, testing, and implementing data extract, transform, and load (ETL) processes. The ideal candidate is a collaborative and analytical data professional with foundational experience developing and supporting data solutions. They have a strong understanding of relational databases, SQL, ETL/ELT concepts, data integration, data transformation, and data quality principles. They enjoy solving data challenges, developing reliable data pipelines, and transforming raw data into accessible information that supports reporting, analytics, and business decision-making. Successful candidates demonstrate the ability to work with data from multiple sources, troubleshoot data processing issues, validate data integrity, and communicate effectively with both technical and non-technical stakeholders. They are detail-oriented, organized, curious, and committed to continuous learning. They are capable of supporting data initiatives throughout the data lifecycle, including requirements gathering, development, testing, documentation, implementation, and ongoing support. The ideal candidate has exposure to modern data technologies, including cloud-based data platforms, APIs, automation, scripting languages, and data engineering frameworks. They are eager to expand their technical skills, collaborate with experienced team members, and contribute to improving enterprise data capabilities. For the Data Warehouse Administrator II, the ideal candidate also brings progressively responsible experience independently designing, implementing, administering, and optimizing enterprise data warehouse solutions.

Requirements

• Sufficient education and increasingly responsible experience to demonstrate possession of the required knowledge, skills, and abilities.
• Development of the required knowledge, skills, and abilities is typically obtained through a combination of training and experience equivalent to graduation from an accredited college or university with a four-year degree in computer science, engineering, business information systems, management information systems, or a closely related field.
• Knowledge of: Data processing tools, techniques, and methodologies; Data warehousing concepts; Information systems development across the IT lifecycle, with a focus on systems to perform high-volume and high-velocity data processing; Relational and NoSQL database technologies; data extraction, querying, and scripting; Implementing business logic using SQL-based transformation frameworks; Database management software and defining hardware requirements; Principles and practices of integrating data from Enterprise Resource Planning and Enterprise Asset Management systems into enterprise data platforms; Relational database theory, structure, principles, and practices; database normalization concepts, data modeling and performance tuning; Software components (e.g., specialized UDFs) and analytics applications; Methods of extracting and integrating data from various sources, for comparative analysis; Troubleshooting techniques for data load or reconciliation; Basic networking principles and concepts; Scripting languages; Software development methodology and release processes; Data visualizations and reporting tools; Data analytics tools, systems, and software troubleshooting; Data management standards, policies, and procedures; Disaster recovery procedures.
• Ability to: Develop, analyze, troubleshoot, and maintain data engineering solutions, including ETL/ELT processes, data pipelines, automation workflows, and supporting application code; Implement statistical modes to identify trends, correlations, and patterns in data sets; Improve and maintain data quality and integrity; Catalog and manage data sources; Maintain, design, and create relational databases and data systems; Design and Build reporting dashboards; Utilize presentation tools to communicate technical information effectively; Mine and analyze data; Perform data cleansing; Develop and maintain technical documentation records; Implement data validation and reconciliation checks to ensure data integrity and Data quality standards; Collaborate with analysts and business stakeholders; Establish and maintain cooperative and effective working relationships with those contacted in the course of business.

Nice To Haves

• Foundational experience developing and supporting data solutions.
• Strong understanding of relational databases, SQL, ETL/ELT concepts, data integration, data transformation, and data quality principles.
• Ability to work with data from multiple sources, troubleshoot data processing issues, validate data integrity, and communicate effectively with both technical and non-technical stakeholders.
• Detail-oriented, organized, curious, and committed to continuous learning.
• Capable of supporting data initiatives throughout the data lifecycle, including requirements gathering, development, testing, documentation, implementation, and ongoing support.
• Exposure to modern data technologies, including cloud-based data platforms, APIs, automation, scripting languages, and data engineering frameworks.
• Eager to expand their technical skills, collaborate with experienced team members, and contribute to improving enterprise data capabilities.
• Progressively responsible experience independently designing, implementing, administering, and optimizing enterprise data warehouse solutions.

Responsibilities

• Develops, implements, and maintains data transformation and automation process using a variety of technologies to support business systems and data flows
• Builds and maintains scalable data pipelines to ingest data into data warehouse from various sources
• Performs data conversions, executes the import and export of data within and between internal and external software systems
• Analyzes source dataset, and data relationship to automate recurring reports and analytics workflows
• Troubleshoots data processing tools, systems, and software applications
• Performs data validation and reconciliation to ensure data accuracy and integrity
• Monitors system performance and capacity in accordance with defined service level agreements
• Maintains the quality and integrity of data repositories by adding, modifying, and deleting data in accordance with established policies and business decisions
• Communicates project status, resolving project issues, problems, and changes
• Administers data processes and quality, and identifies opportunities to improve data reliability and efficiency
• Administers system performance and capacity, and identifies potential infrastructure improvements as needed
• Assists in preparing and updating technical documentation, such as data mappings, specifications, data dictionaries, and support materials
• Develops and maintains application programming interfaces (APIs) to support data accessibility and third-party integration
• Maintains the data dictionaries and related metadata documentation
• Supports self-service analytics by publishing certified datasets and reusable pipelines
• Maintains technical and functional competency in applications utilized by to collect and analyze data in the organization
• Performs related duties as required

Benefits

• Family-Friendly Workplace Certification Program (FFWCP) recognizes VTA as a business that creates supportive workplaces for employees and their families.
• Family-friendly workplaces improve health outcomes and job satisfaction for employees and increase work productivity and retention for employers.
• Employers can create a family-friendly workplace by meeting and exceeding state and federal employment laws relating to parental leave, lactation accommodation, and work/family balance.

What This Job Offers

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