The Cradle-to-Career Data System (C2C) is a new state investment that will be crucial to help give students and families the information they need to pursue their dreams. C2C will help the state develop public policy based on reliable and actionable information. The current challenges facing the state clarify the difficulty of using disconnected data systems to understand and respond to public health, economic, and social justice crises.
The California Government Operations Agency (GovOps) will house C2C and is currently setting up the managing entity that will steward this important work. GovOps is an agency that focuses on improving statewide programs and operations and is well-positioned to house the managing entity for the C2C system as a neutral entity that works with departments across the State. You will join a team of friendly, passionate, civic-minded individuals that care about giving the best services possible to Californians.
You will be central to making sure the Cradle-to-Career data model and system approach is architected to support a range of uses and ensure it is flexible enough to incorporate future datasets and user needs. You’ll work closely with the project team to evaluate the data model fit and flexibility and system approach and provide ongoing feedback and support to the team. This will be informed by your close work with the project team and stakeholders to refine user needs into conceptual and logical data models and data system requirements. Most importantly, your work will be challenging, fun and impact the lives of Californians.
Salary and Duration
The Data Architect role is full-time for 9 months, salary range is $10,356.00 - $12,902 / month.
Key Objectives and Responsibilities
Co-develop, with project team, conceptual and logical data model and system requirements to support the C2C vision and issue a request for services
Work closely with project team to validate and refine end user input and feedback on their needs for analytical data products including beyond the pilot
Assist in drafting and reviewing data models with the project team and collecting and incorporating feedback from stakeholders
Review proposed data models with future needs in mind, evaluating for flexibility
Provide working proofs of concept as needed to help in the evaluation of data models
Develop technical and data system requirements consistent with a modern, cloud-based stack to be used in procurement documents
Oversee and guide implementation of data processing and data warehousing to produce analytical datasets
Help develop technical implementation plans for data partitioning, data normalization/denormalization, data aggregations and ETL/ELT
Review and provide input on data quality requirements and verification tests for data model validation
Help design and oversee data processing workflows to cleanse, standardize, deduplicate, and match data from partner entity data sets
Develop cost estimates for right-sizing cloud-based technical components (data warehouse, data processing system, data storage, and other supporting tools) taking into account scaling needs over time and balancing cost with performance
Participate in the selection of qualified vendors for implementation
Monitor technical implementation and ensure systems are developing per plan and with excellence
Extend and support data system implementation as needed
Test performance and troubleshoot issues where necessary; propose and implement appropriate solutions
Provide project implementation support including code/workflow review and testing if necessary to support the project team
Advise on improvements to primary data systems feeding analytical and operational tools
5+ years of experience building data warehouse environments and data processing workflows using cloud infrastructure and services
5+ years of leadership experience relating to database modeling, data normalization, database design, ETL technologies, data pipelines and data products
Advanced level knowledge of SQL with very strong relational database and data warehousing knowledge
3+ years of experience working with commercial data management tools or other comparable set of tools OR commitment and willingness to rapidly self-teach
Experience with at least one project involving highly sensitive data including personally identifiable information
2+ years of experience with Snowflake or similar cloud data platform and warehouse