Top Data & Analytics Jobs

Processes, analyzes, validates, and quality-controls LiDAR, point cloud, aerial imagery, and other geospatial datasets. Produces maps, terrain and surface models, contours, orthomosaics, 3D models, and infrastructure-focused deliverables. Supports GIS data management, utility GIS, spatial analysis, schema development, web maps, field data solutions, and automation using Python and related tools. Collaborates with engineers, surveyors, GIS professionals, and project managers to troubleshoot data issues and improve repeatable geospatial workflows.

Design, build, and maintain ETL/ELT pipelines and SSAS tabular models. Develop complex T-SQL queries and Power BI reports. Ensure data quality, optimize performance, and support migration of legacy systems into Microsoft BI environments while collaborating with stakeholders.

Leads the Prospect Research and Analysis team supporting college advancement and fundraising strategy. Oversees prospect identification, data validation, research methodologies, deep-dive analysis, intelligence gathering, visualization, reporting, and briefing materials. Develops actionable recommendations, expands donor prospect pools, forecasts trends, improves research processes, and manages cross-functional initiatives. Supervises staff, partners with senior administration and fundraising leadership, and promotes data integrity, confidentiality, innovation, and collaboration.

Design, build, deploy, and operationalize scalable data engineering solutions for customers. Responsibilities include developing pipelines, transforming and cleansing data, analyzing sources, implementing governance, security, and quality practices, testing data movement and transformation code, resolving defects and incidents, and advising customers on technical decisions. The role also supports AI, machine learning, business intelligence, and data product adoption while collaborating across teams and educating end users.

Drive mobile app growth through ad-hoc SQL analysis, dashboards, and BI tools; partner with CEO/CFO to provide insights, streamline ETL/ELT pipelines, and optimize user acquisition, retention, and monetization.

Provides business intelligence and credit risk analytics for banking portfolios. Partners with business leaders to translate strategic issues into data extracts, reports, analyses, and recommendations. Researches loan and deposit trends, supports reporting platforms and CRM business rules, validates BI development needs, identifies data gaps, and presents complex findings clearly. Collaborates with marketing, data management, and business intelligence teams to improve reporting and decision-making.

Produces, validates, reconciles, and distributes operational and client reports, invoice detail packages, and collections letter campaign output. Investigates data discrepancies, monitors service-level and productivity metrics, documents corrective actions, and supports compliance, audit readiness, and production controls. Collaborates with Collections leadership, IT, and Dialer Administration while maintaining report specifications, procedures, and distribution processes.

Lead modernization of data platforms, design and maintain ETL/ELT pipelines and data warehouse models, improve data governance and quality, optimize platform performance, and collaborate with IT, business units, and leadership to drive data-driven initiatives and stakeholder alignment.

Leads enterprise master data governance across customer, product, supplier, and transaction domains. Establishes data standards, architecture, quality metrics, systems of record, and warehouse structures. Partners with IT, analytics, and business leaders to enable reliable reporting, AI, customer segmentation, pricing, sourcing, and operational insights. Drives data cleanup, enrichment, continuous improvement, cross-functional governance, training, and data literacy while maintaining business ownership and accountability for enterprise information integrity.

As a Data Engineer, you will create efficient data models, pipelines, and analytics frameworks, collaborating with various departments to transform raw data into actionable insights.