Top Data & Analytics Jobs

Provide forecasting and analytics to optimize staffing, scheduling and workforce allocation across customer care, collections, fraud and other operations. Analyze large datasets to produce demand forecasts and staffing plans, recommend process improvements, support operational readiness, manage stakeholder relationships, and uphold risk and control standards.

Creates and maintains GIS databases, maps, metadata, and utility network drawings using survey, LiDAR, environmental, transportation, and utility data. Collaborates with engineers and surveyors, performs GIS analysis, supports multiple projects, documents workflows, and identifies process improvements. Uses ArcGIS, AutoCAD, Google Earth, and related software while serving as a primary GIS contact on large projects.

Designs trusted Snowflake data products and enterprise semantic models that standardize business concepts, metrics, relationships, and rules. Builds Cortex semantic views and agents, validates AI-generated results, develops regression tests, and maintains metadata, lineage, and documentation. Leads modeling initiatives from discovery through production while partnering with business and technical stakeholders to improve analytics, automation, and AI consistency.

Analyzes complex healthcare and revenue cycle data to identify trends, measure operational and financial performance, and provide actionable recommendations. Develops reports, dashboards, analytical models, and structured datasets using SQL, Databricks, and BI tools. Partners with cross-functional teams to define requirements, validate data, communicate insights, and support continuous improvement initiatives.

Designs, builds, secures, monitors, and supports scalable data platforms across public and multi-cloud environments. Develops batch and streaming pipelines, ELT processes, data lakes, warehouses, APIs, and integrations with transactional systems. Works with SQL and NoSQL databases and technologies including Spark, Hadoop, Databricks, Snowflake, Kinesis, and Lambda. Leads projects, presents to leadership, collaborates with clients and Scrum teams, troubleshoots issues, and enables analytics and machine learning initiatives.

Own the end-to-end client reporting process, including report templates, data population, quality assurance, scheduling, documentation, and delivery. Build and maintain Looker Studio reports using data from analytics, advertising, CRM, and search platforms. Coordinate handoffs to channel specialists and account managers, identify data issues, and improve reporting efficiency through AI, automation, and standardized workflows.

Designs and oversees enterprise data architectures spanning databases, warehouses, lakes, integrations, and cloud environments. Translates business requirements into scalable, secure, and cost-efficient solutions; establishes data modeling, governance, quality, metadata, and security practices; guides engineers and analysts; optimizes infrastructure; and maintains architecture documentation. Requires extensive Databricks, data engineering, big data, cloud, and stakeholder leadership experience.

Leads modernization of Lazard Asset Management’s data estate by defining enterprise data strategy, migrating legacy systems to a cloud-native platform, establishing DataOps, and delivering governed data products and APIs. The role owns architecture, security, regulatory controls, operational KPIs, AI-ready data, and production-safe migrations while building and mentoring a high-performing data engineering team.

Supports nonprofit program evaluation by analyzing outcomes, managing survey and participation data, monitoring metrics, preparing funder reports, and creating dashboards. The intern researches best practices in survey design and outcome measurement and collaborates with program leaders to use data to improve services and outreach. This is a hybrid, part-time spring internship requiring 16–24 hours weekly, with occasional travel to program sites.

Owns enterprise data quality, governance, metadata, lineage, and master data management across operational and analytical domains. Ensures data meets business, policy, regulatory, and contractual requirements; drives consistent metric definitions; oversees data issue resolution, compliance reviews, and quality standards throughout the data supply chain. Partners with business stakeholders, IT, engineering, risk, and compliance teams, and provides training on appropriate data usage.