License and Certification Qualifications: None required Education Qualifications: High school diploma or equivalent required. Bachelor's degree in related field preferred. Experience Qualifications: Six years of experience building and operating distributed systems of data extraction, ingestion, and processing of large data sets from multiple sources. Expert command of SQL (Structured Query Language) with experience building database tables. Experience optimizing queries and utilization of server resources for performance and efficiency. Experience ingesting and combining raw and unstructured data of various types. Experience working across multiple deployment environments, multiple operating systems, and various containerization techniques. Experience with non-relational databases preferred. Experience with popular open-source and commercial data science platforms (e.g. Python, R) preferred. Skills Qualifications: Demonstrated skill and ability to develop and manage scalable data integration processes for a large school district; ability to develop an analytical infrastructure to support various applications, including business intelligence tools, software applications, and analysis to produce meaningful insights; ability to communicate effectively and to work well with others; strong organizational skills and the ability to multitask; ability to work across functional boundaries and interact with employees at all levels of the organization. Primary Responsibilities: Responsible for the design, development, testing, implementation, and maintenance of data integration processes.
1. Contribute to the development of a modern data infrastructure that drives decision-making at all levels of the organization.
2. Develop and maintain scalable data pipelines and build out new integrations to support increasing data volume and complexity.
3. Optimize existing ETL (Extract, transform, load) processes and data integration and data preparation flows and helping to move them in production. a. Extract, transform, and load data from raw unstructured data to consumable structured data.
4. Collaborate with stakeholders, developers, and department management to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision-making across the organization.
5. Implement processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
6. Work with data governance and data security teams in moving data pipelines into production with appropriate data quality, governance and security standards and certification. a. Guarantee compliance with data governance and data security requirements.
7. Design, build, and manage data pipelines for data structures encompassing data transformation, data models, schemas, metadata and workload management.
8. Drive automation through effective metadata management using innovative and modern tools, techniques, and architectures.
9. Explore ways to enhance data quality and reliability.