Top Data & Analytics Jobs

Build and maintain Snowflake data pipelines, integrations, data models, reconciliation checks, backend services, and internal automation tools. Develop production AI workflows using Claude, MCP, and managed model platforms for document retrieval, extraction, and understanding. Own solutions through design, deployment, monitoring, documentation, and support while protecting sensitive financial data and collaborating with operations, compliance, vendors, and technical stakeholders.

Supports renewable energy projects through spatial analysis, cartography, GIS data management, mapping, field data collection, PDF reporting, quality control, and technical troubleshooting. Creates ArcGIS Online Field Maps, maintains geospatial data integrity, develops mapping products, performs complex analyses, and builds scripts or tools to streamline recurring tasks. Collaborates with project teams and end users while improving GIS workflows and supporting energy-sector projects.

Build scalable data ingestion, transformation, entity resolution, and integration pipelines for a cybersecurity ontology and knowledge graph platform. Design batch and real-time distributed systems processing billions of security events, ensure data quality and governance, model entities and relationships, and enable AI agents through structured security knowledge and ontology APIs.

Annotate and label images and video from humanoid robots using proprietary tools, collaborate with ML engineers on guidelines, flag edge cases, maintain quality and throughput, and provide feedback to improve workflows.

Lead analytics for Wealth Solutions: analyze client segmentation, revenue, and operational data; build models for capacity and workforce planning; produce insights and recommendations for senior leadership; partner with BI and Finance to improve advisor productivity, client experience, retention, and revenue growth; support strategic projects and translate complex data into clear presentations.

Build and maintain analytics-ready data models in Databricks, including Gold and Platinum layers, semantic metrics, AI/BI datasets, and documentation. Develop SQL and Python transformations, validate data against systems of record, maintain lineage, troubleshoot Redshift assets, and support Tableau reporting. The role requires collaboration with business stakeholders, adherence to data modeling and governance standards, and communication of technical concepts to nontechnical audiences.

Develops and supports ETL workflows, REST APIs, backend services, AWS file-transfer automation, legacy applications, and data-processing systems. Troubleshoots production issues, manages deployments across environments, improves monitoring and recovery, and documents technical systems. Requires SQL, relational database, API, data integration, batch-processing, and production support experience, along with U.S. citizenship and the ability to pass a Public Trust investigation.

Provides intermediate-level analysis, implementation, integration, support, and troubleshooting for business systems and data solutions. Translates business requirements into technical specifications, supports system development lifecycle activities, manages changes and releases, resolves production issues, documents IT processes, and collaborates with business and IT teams. The role uses SQL, ETL, Databricks, Azure, relational databases, BI tools, and ServiceNow.

Manages Finance analytics engineering and automation, building governed Snowflake and SQL data products, consumption layers, reconciliations, controls, workflows, and integrations. Partners with FP&A, Data Engineering, and business teams to translate Finance requirements into reliable technical solutions. Leads lineage analysis, testing, monitoring, documentation, AI-assisted workflows, production support, and team development while maintaining clear ownership between Finance and enterprise data teams.

The Associate Director will lead AHP’s analytics and data products domain, building curated datasets, transformation pipelines, semantic models, dashboards, and automated reporting. Responsibilities include delivering client and enterprise data products, establishing reporting standards, managing production refreshes and documentation, coordinating data engineering resources, and supporting AI initiatives. The role is hands-on, client-facing, and requires technical leadership across distributed project teams.