Top Data & Analytics Jobs

Leads enterprise data warehousing, data engineering, governance, security, and AI-enabled data initiatives. Oversees AWS Redshift and Informatica-based platforms, ETL pipelines, data models, quality, lineage, metadata, testing, and regulatory compliance. Drives architecture modernization, production issue resolution, CI/CD integration, and responsible AI governance. Partners with executives, technology, risk, compliance, product, and business teams while managing vendors, budgets, and a large data engineering team.

Analyzes field service, technical support, call, and operational data to identify root causes, validate information, improve processes, reduce service issues, and enhance performance. Responsibilities include monitoring work levels, reviewing technical content, managing DIY operations, handling escalated cases, preparing reports and cost analyses, supporting pilot tests, coordinating with factories and departments, and communicating performance insights to leadership.

Build and maintain Power BI dashboards, reports, semantic models, and executive scorecards using Microsoft Fabric, SQL, DAX, and Azure data services. Design lakehouses, data pipelines, ELT processes, and governed BI assets connecting ERP, MES, OT, and WMS data. Troubleshoot performance and data quality issues, support governance and lineage documentation, gather requirements, conduct testing and demos, and provide technical guidance to other BI analysts.

Validate and monitor risk signals used for transaction monitoring, fraud scoring, and rule-based alerting. Ingest, cleanse, transform, and assess data quality; maintain dashboards, scorecards, and documentation; support root-cause analysis, KPIs/KRIs, and remediation; collaborate with Compliance, Data, and Risk teams to refine detection logic and inform model/rule improvements.

Lead the end-to-end migration of quote-to-cash data from Salesforce CPQ and NetSuite into Salesforce Revenue Cloud Advanced and Oracle. Define migration architecture, design ETL pipelines, map and transform complex commercial and financial data, manage cleansing and reconciliation, optimize bulk loads, and lead distributed ETL developers. Produce migration specifications, runbooks, cutover plans, and audit-ready reconciliation reports while coordinating with Finance, Sales Operations, IT, and executive stakeholders.

Build and own production data pipelines, warehouse models, metric definitions, testing, monitoring, reconciliation, and alerting. Partner with Finance and other teams to create reliable datasets for usage, revenue, costs, margins, reporting, self-service analysis, and AI-assisted querying. Improve source data quality, investigate discrepancies, and establish a maintainable data foundation.

Designs, administers, and evolves Fisher Investments’ Azure data warehouse and analytics platform. Responsibilities include developing cloud data solutions, setting architecture and security standards, guiding developers, troubleshooting systems, monitoring operations, planning capacity, optimizing cloud costs, and supporting BI and data delivery teams. The role also coordinates cross-functional projects, provides after-hours support, and prepares technical work plans and status reports.

Own client relationships and analytics strategy across digital measurement and GEO initiatives. Architect, audit, and QA GA4 and Adobe Analytics implementations; develop measurement frameworks, dashboards, experimentation plans, and causal analyses. Present insights to executive stakeholders, manage analytics workstreams, mentor teammates, and build AI-assisted workflows, automations, and scalable systems. The role combines traditional analytics with measurement of AI-powered search visibility and customer behavior.

Leads commercial real estate research, analytics, forecasting, risk analysis, and market intelligence using diverse economic, financial, lending, and real estate data. Oversees research tools, models, databases, and quality processes; communicates findings through reports, presentations, webinars, podcasts, and client materials. Mentors team members, partners with Client Services, and standardizes analytical and reporting practices across the Research Group.

Leads the design and implementation of scalable data models, pipelines, and analytics systems. Collaborates with data scientists, product analysts, software engineers, and stakeholders on cross-functional initiatives. Ensures data quality, testing, validation, observability, security, and system reliability while using AI to improve analytical engineering workflows and automate routine tasks.