Data Engineer

SAN DIEGO WORKFORCE PARTNERSHIP INC•San Diego, CA

19h•$95,805 - $130,946

About The Position

Under the supervision of the CFO, the Data Engineer is responsible for designing, building, maintaining, and optimizing the organization's data infrastructure to support reporting, analytics, program performance measurement, and data-driven decision-making. This role develops and manages data pipelines, integrations, databases, and data architecture that ensure reliable, secure, and accessible data across the organization. Working closely with program teams, leadership, IT, and data analysts, the Data Engineer transforms complex and disparate data sources into scalable solutions that support business intelligence, operational reporting, compliance requirements, and strategic initiatives. Playing a critical role in ensuring data quality, integrity, governance, and accessibility while supporting organizational goals through efficient data management practices. The Data Engineer stays current on emerging technologies, industry trends, and best practices in data engineering, cloud platforms, data warehousing, automation, and system integration. Success in this role is measured by the reliability and scalability of data systems, the accuracy and availability of organizational data, and the ability to enable meaningful insights that support workforce development outcomes, operational excellence, and strategic decision-making.

Requirements

Bachelor’s degree in computer science, data science, information systems or related field.
Three to five (3-5) years of professional experience as a Data Engineer, Data Scientist, Business Intelligence Developer or relevant data focused role.
Strong proficiency in SQL Server, PostgreSQL and experience querying, manipulating, and optimizing large datasets; identifying trends, patterns, and actionable insights.
Working knowledge of programming languages such as Python, R, or similar languages used for data processing, automation, and analytics.
Experience with business intelligence and data visualization platforms such as Domo, Microsoft Power BI, Tableau, business intelligence or similar platforms.
Experience working with Customer Relationship Management (CRM) systems such as Salesforce, Microsoft Dynamics, or similar enterprise platforms.
Knowledge of relational databases, data warehousing concepts, data modeling, and database design principles.
Experience designing and implementing data architectures that support reporting, analytics, and organizational decision-making.
Understanding of data governance, data quality, data security, and data management best practices.
Experience developing visualizations, dashboards, and reports that effectively communicate business performance and outcomes.
Knowledge of statistical analysis techniques and data validation methodologies.
Ability to troubleshoot complex data issues and develop effective technical solutions.
Ability to manage multiple priorities and meet deadlines in a fast-paced environment.
Ability to collaborate effectively with technical and non-technical stakeholders across all levels of the organization.
ETL and data integration tools.
Strong organizational skills, high attention to detail, coupled with strong written, verbal, and interpersonal communication skills.
Computer proficiency, particularly with the Microsoft Office suite, including Outlook, Word, Excel and PowerPoint

Nice To Haves

Master’s degree in computer science, data science, information systems or relevant field.
Experience supporting workforce development, nonprofit, public sector, government-funded, or grant-funded programs.
Experience with workforce development performance metrics, compliance reporting, and outcome measurement.
Experience leading or supporting business intelligence platform migrations, including transitions from Domo to Power BI or similar environments.
Experience implementing automation and process improvement initiatives that increase efficiency and reduce manual reporting efforts.
Cloud-based data and analytics platforms preferred.
Experience supporting data migration efforts and analytics platform transitions is highly desirable.

Responsibilities

Design, develop, implement, and maintain scalable data architectures, databases, data warehouses, and data pipelines that support organizational reporting, analytics, and business intelligence needs.
Manage data engineering projects from initiation through completion, ensuring objectives, timelines, and deliverables are achieved.
Collaborate with IT, program teams, leadership, and cross-functional stakeholders to identify data requirements, source systems, and integration opportunities.
Design, develop, and maintain automated Extract, Transform, and Load (ETL) processes to support data ingestion, transformation, validation, and reporting.
Organize, integrate, and consolidate data from multiple internal and external systems while ensuring data accuracy, consistency, and integrity.
Develop and implement data quality assurance processes, monitoring procedures, and validation controls to ensure reliable and trustworthy data.
Analyze, process, evaluate, and document large and complex datasets to support operational, compliance, and strategic initiatives.
Design and optimize data structures, storage solutions, and data models that support efficient data retrieval, reporting, and advanced analytics.
Develop scalable and automated processes to support large-scale data management, reporting, analytics, and predictive modeling efforts.
Support the organization's growing analytics and reporting needs by creating sustainable data infrastructure and improving data accessibility for end users.
Design, architect, implement, and maintain new and existing data pipelines while identifying opportunities for performance improvements and process automation.
Refactor and modernize legacy data processes to improve efficiency, reliability, scalability, and maintainability.
Maintain and enhance the organization's data analytics environment, ensuring systems remain secure, effective, and aligned with business needs.
Evaluate emerging technologies, industry trends, and best practices related to data engineering, analytics, automation, and cloud-based solutions.
Develop technical documentation, data dictionaries, workflow diagrams, and system architecture documentation to support operational continuity and knowledge transfer.
Support business intelligence initiatives by preparing and optimizing data for dashboards, reports, visualizations, and decision-support tools.
Lead data migration and system transition efforts, including planning, testing, validation, and implementation activities associated with the organization's transition from Domo to Power BI and other future analytics platforms.
Provide technical expertise and recommendations regarding data governance, data management standards, security, privacy, and compliance requirements.
Troubleshoot and resolve data integration, pipeline, database, and reporting issues to minimize disruption to organizational operations.
Partner with leadership and business stakeholders to identify opportunities to leverage data as a strategic asset and improve organizational performance through data-driven decision making.
Perform other related duties as assigned.