Top Data & Analytics Jobs

Lead administration and architecture of the Blackbaud Raiser's Edge NXT database to ensure data integrity, integrations, governance and reporting. Build data strategy and 360-degree donor profiles, create complex queries/exports, manage ETL and integrations, support fundraising and alumni engagement campaigns, drive adoption and KPIs, and partner with cross-functional teams to optimize CRM, analytics, and technology roadmap.

Supports client data integration by analyzing file structures, creating source-to-target mappings, configuring imports, validating transformations, troubleshooting ingestion failures, and supporting onboarding. The role performs testing, production support, documentation, and process improvement while collaborating with clients, QA, implementation managers, and ETL developers. It requires data mapping, ETL familiarity, SQL knowledge, and experience handling CSV, XML, and JSON files.

Lead social media measurement and analytics across paid and organic channels. Own KPI frameworks, ensure data integrity, manage dashboards and disparate data sources, and translate performance data into executive-level insights. Identify campaign trends and efficiency opportunities, recommend strategic pivots, and partner with creative, media, and strategy teams on forecasting, A/B testing, investment decisions, and stakeholder communications.

Build and maintain facility maintenance performance dashboards, monthly reports, cost-avoidance analyses, and failure/lifecycle analyses. Define metrics with government customers, validate data quality, document data sources and calculation rules, support parts-demand planning, and explain data issues to operations staff. The role requires SQL, dashboard design, data visualization, and compliance with sensitive-data and CUI handling practices.

Maintains and develops data sets, dashboards, reports, and automated ETL processes. Administers SharePoint, Teams, and assigned commercial or funder platforms; troubleshoots analytics systems; supports data security and operational improvement. Partners with agency leaders to define reporting needs, establishes data standards, provides analytics guidance, and trains users on data tools and platforms.

Analyze sales, marketing, and operational data to create dashboards, reports, predictive models, and business insights. Lead data projects, build data models and pipelines, maintain reporting accuracy, support governance and quality initiatives, and communicate findings to nontechnical stakeholders. Collaborate with leadership and cross-functional teams to improve performance, forecasting, and operational efficiency.

The Senior Data Engineer designs and maintains production data pipelines on GCP using BigQuery, Dataform, Airflow, Dataflow, and Cloud Run. They own data validation, cleansing, troubleshooting, API integrations, and reliable datasets for analytics and AI/ML. The role also involves translating client requirements into data solutions, maintaining dashboards, supporting ad hoc requests, and applying Git, code reviews, and CI/CD practices.

Manages advancement CRM systems, data integrity, fundraising and financial reporting, prospect research, donor analytics, and staff CRM support. Identifies and qualifies major-donor prospects, maintains constituent intelligence, and supports portfolio and moves management. Coordinates advancement services, alumni and donor communications, web updates, and special projects while collaborating with development leadership, gift officers, marketing, IT, and university departments.

Designs, deploys, maintains, scales, and supports enterprise database systems, primarily PostgreSQL in Linux environments. Responsibilities include database architecture, tuning, backup and recovery, failover, large-scale data management, ETL, operational support, testing with real data, and developing system features. The role also explores emerging technologies, supports customer facilities, and may contribute to cloud, DevOps, GIS, APIs, dashboards, and web development.

Provide analytic and consultative support to internal customers; translate requirements into decision-support applications; model data flows; develop complex programs and reports (SAS, R, SQL) using enterprise databases; propose and lead data-driven solutions; prepare findings and presentations for stakeholders; define data policies and security frameworks.