Top Data & Analytics Jobs

Lead product data engineering across architecture, data modeling, pipelines, monitoring, lineage, and data quality. Build reliable analytical datasets, support experimentation and machine learning use cases, and resolve business-critical pipeline issues. Partner with product and engineering stakeholders to translate business needs into automated data solutions. The role requires ownership of end-to-end data engineering projects, on-call participation, and development of AI-assisted monitoring and automation.

Design and maintain data architecture and pipelines to support compliance and risk teams. Build and optimize data models, standardize metrics, and create data dictionaries. Implement data quality, lineage monitoring, AI-driven agents for false-positive reduction and automation, and participate in on-call rotations to ensure SLAs are met.

Analyze workforce, talent, organizational health, and employee experience data to support senior People leaders. Build dashboards, reports, and scalable insight products; use AI to automate analyses; translate ambiguous questions into recommendations; create executive-ready storytelling; improve data quality and self-service reporting; and partner with People, data, and systems teams while protecting sensitive employee information.

Own end-to-end analytics engineering for AI and developer-experience telemetry, including instrumentation, production pipelines, governed metrics, monitoring, executive dashboards, and analysis. Define and validate new measures of AI productivity and ROI, communicate findings to senior stakeholders, and recommend improvements to tooling, processes, and investment. Collaborate with data engineering, applied AI, and data science teams while using AI coding agents to build and maintain pipelines and reporting.

Own end-to-end analytics engineering for AI and developer experience data. Instrument telemetry, build governed production pipelines, define trusted metrics, and create executive-facing dashboards and analyses. Partner with data engineering, AI, and data science teams to improve data quality and connect raw signals to decision-making. Present clear recommendations on AI investment, developer productivity, and ROI while using AI coding agents to build and maintain pipelines, dashboards, and analyses.

Own end-to-end reconciliation and reporting for card networks, banks, processors, and internal ledger data. Build SQL-based reporting, dashboards, exception queues, metrics, controls, and automated solutions; investigate discrepancies, improve data quality, support month-end close and audits, and partner with Engineering, Product, Accounting, Treasury, Tax, and Compliance. The role also defines requirements and test plans, maintains data pipelines, mentors analysts, and drives automation across payment settlement and money-movement processes.