Top Data & Analytics Jobs

The Manager, Identity Fraud Strategy oversees identity verification and authentication strategies, leads a fraud analytics team, and partners with CIAM to minimize fraud while enhancing customer experience.

Lead architecture and buildout of a new graph-backed enterprise data platform: design ingestion, graph and relational storage, entity resolution pipelines, temporal models, ETL/ELT pipelines, governance, APIs, and production connectors. Ship scalable graph data models, traversal queries, and platform roadmap while enabling observability, security, and containerized deployments.

As an SEO Analyst, you will analyze data to improve SEO strategies, provide performance reports, and collaborate with teams to enhance user experiences and brand visibility.

Own and architect large-scale data pipelines, orchestration, and integrations. Drive IaC strategy (Terraform), third-party API and AI/LLM tool integrations, build export pipelines and internal tooling, mentor engineers, and align cross-team technical strategy for reliable, scalable data infrastructure.

Build and maintain ELT pipelines, data models, semantic layers, and personalization signals for client retention and marketing tests. Partner with machine learning, product, marketing, design, and architecture teams to prepare predictive data, connect signals to CRM channels, support real-time event processing, and document a scalable data foundation. Use AI coding assistants daily to accelerate development, testing, and reviews in a fast-moving discovery environment.

Serve as the analytics lead for Acuity Scheduling: build data infrastructure, dashboards, and monitoring; translate product, financial, and operational data into executive insights; design metrics frameworks; run weekly/monthly reviews and deep dives; partner with Product, Engineering, and Analytics to support growth, retention, and strategic decision-making.

Designs scalable data models, governance processes, quality checks, documentation, and internal data tools. Partners with Data Engineering and business stakeholders to create trustworthy, discoverable, AI-ready data assets supporting analytics, reporting, downstream applications, and machine learning initiatives. Uses AI tools to improve modeling, governance, analysis, documentation, and automation workflows.

Lead design and development of BI information models, dashboards, metrics, and Palantir visualizations. Translate stakeholder requirements into technical reporting solutions, use SQL and programming tools to acquire, transform, validate, and visualize data, document metric logic, and support maintenance. Partner with business and technical teams, ensure scalable accurate BI solutions, and drive analytics that improve operational and strategic decision-making. Onsite at Hazelwood, MO; requires active U.S. Secret clearance.

Build and lead the data engineering ecosystem supporting analytics, BI, and data science. Design scalable pipelines, cloud infrastructure, Snowflake data warehouses, governance controls, validation frameworks, and machine learning workflows. Collaborate with engineering, data science, product, and business stakeholders on architecture and technology decisions. Develop AI agents and secure enterprise AI integrations, participate in on-call and incident management, document standards, and mentor data engineers.

Analyze customer data and build production-grade data models, dashboards, data products, and self-service analytics capabilities. Automate manual workflows, translate stakeholder needs into scalable solutions, and experiment with generative AI, conversational analytics, and AI-assisted coding tools. The role requires strong SQL, data visualization, analytical problem-solving, business judgment, communication, and collaboration skills. This is a hybrid position requiring three days onsite weekly in Framingham.