Data Engineer-Enterprise Data, Governance,Integration, Analytics

National Council on AgingArlington, VA
$88,258 - $102,345

About The Position

We are seeking a dynamic, visionary Data Engineer, Enterprise Data, Governance, Integration & Analytics to bring their expertise, creativity, and strategic leadership to help drive our mission while embodying NCOA's core values of Caring for All, Collaboration, Innovation, Integrity, and Respect. This highly collaborative role combines hands-on data engineering with enterprise integration, data governance, analytics enablement, and stakeholder partnership. The ideal candidate will be equally comfortable building a reliable data pipeline, documenting and cataloging a data asset, and working directly with business users to translate an operational need into an adopted solution. At NCOA, we are on a mission to create the conditions for all to age well in America—today and into the future. Every day, we work to improve the lives of millions of older adults through innovative programs, trusted advocacy, strategic partnerships, and evidence-based solutions that advance health, economic security, and equity. If you are passionate about using the power of data to create measurable social impact, we invite you to join us in transforming the future of aging in America.

Requirements

  • Bachelor’s degree in information technology, Computer Science, Data Analytics, Information Systems, or a related field, or equivalent combination of education and relevant experience.
  • 2–4 years of relevant experience in data engineering, analytics engineering, business intelligence, database administration, systems integration, or related work.
  • Experience with relational database management systems, SQL, data modeling, and analytics-ready dataset design.
  • Experience designing, maintaining, or improving ETL/ELT pipelines, data transformations, data integrations, or automated data workflows.
  • Experience with data cataloging, metadata management, data documentation, governance practices, or data stewardship workflows; experience with data.world preferred.
  • Exposure to reporting, dashboards, and analytics platforms such as Power BI,QuickSight, Tableau, Salesforce reporting, or comparable tools.
  • Experience gathering requirements, defining project scope, documenting decisions, and using data to generate business insights.
  • Ability to use AI-assisted tools responsibly to support development, documentation, analysis, testing, and productivity.
  • Strong customer service, stakeholder communication, and expectation-setting skills.
  • Excellent analytical, organizational, and problem-solving skills, including the ability to manage multiple priorities in a dynamic environment.
  • Strong critical thinking skills and a desire to take initiative, learn new technologies, and improve existing processes.

Nice To Haves

  • Understanding of ETL/ELT concepts, including data flow, enrichment, consolidation, change data capture, transformation, orchestration, and monitoring.
  • Understanding database concepts such as referential integrity, indexing, keys, schemas, table metadata, query optimization, and data quality.
  • Hands-on experience with cloud data platforms or services such as AWS, Azure, SQL Server, S3, Glue, DynamoDB, RDS, Redshift, or comparable technologies.
  • Experience with Microsoft business and data tools such as Fabric,Power BI, Excel PowerPivot, Power Apps, Power Automate, Azure App Service, Microsoft 365 Copilot, or comparable tools.
  • Experience with Salesforce Sales Cloud, Experience Cloud, Nonprofit Success Pack, Marketing Cloud, or related CRM and marketing technologies.
  • Experience with workflow automation and work-management tools such as Zapier, Asana, Power Automate, or comparable platforms.
  • Experience with Git, CI/CD pipelines, testing, documentation, and deployment practices in an analytics or data-engineering environment.
  • Experience with containerization, infrastructure-as-code, APIs, or modern application integration patterns.
  • Familiarity with responsible AI practices, including appropriate review of AI-generated code, protection of sensitive data, documentation of assumptions, and validation of outputs.
  • Knowledge of nonprofit operations, aging services, benefits access, advocacy, or mission-driven organizations.

Responsibilities

  • Partners with internal business teams to define key business questions, translate requirements, and build datasets, automations, and reporting solutions that address organizational needs.
  • Design, build, test, document, and maintain data pipelines, data models, and analytics-ready datasets.
  • Serve as the technical and operational lead for NCOA’s data.worlddata catalog, including catalog configuration, metadata standards, data asset documentation, business glossary support, lineage and ownership practices, stakeholder onboarding, and ongoing adoption across teams.
  • Develop and maintain ETL/ELT processes, data transformations, data quality checks, and workflow automations across organizational systems.
  • Use AI-assisted development and productivity tools, including OpenAI Codex, Microsoft Copilot, and embedded AI features in enterprise platforms, to improve engineering, documentation, testing, analysis, and automation workflows while following security and responsible-use expectations.
  • Design, maintain, and troubleshoot workflow automations using tools such as Zapier and Asana, ensuring data movement, task creation, notifications, and cross-system handoffs are reliable, documented, and aligned with business processes.
  • Prototype, validate, and productionize reporting, automation, and data-product solutions in partnership with stakeholders.
  • Collaborate with data science, analytics, enterprise applications, and business stakeholders to improve data access, data literacy, governance, and operational decision-making.
  • Document technical solutions, data definitions, lineage, processes, automations, and support procedures.
  • Analyze, understand, and create ETL automation for data sources that serve the needs of internal users and data scientists.
  • Other duties as assigned.

Benefits

  • Competitive and equitable compensation
  • Geographic pay structure
  • Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
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