Top Data & Analytics Jobs

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.

Own data strategy for a business unit, ensuring data readiness for AI initiatives. Assess data quality, accessibility, lineage, and suitability; partner with engineering teams on data preparation, transformation, ontology design, and knowledge-base construction. Define data roadmaps, integration priorities, governance frameworks, and quality standards for AI and agentic workflows. Translate strategy and technical trade-offs for executives and cross-functional teams.

Supports CRM, data management, BIO, and business teams by assessing impacts, documenting implementation-ready requirements, resolving dependencies, and prioritizing delivery. Performs data profiling, discrepancy investigation, mapping validation, reporting impact analysis, and business-rule documentation. Facilitates stakeholders, coordinates delivery, and works with Salesforce and Veeva Vault CRM specialists using SQL, Python, Jira, and Confluence.

Develops and oversees data strategies and architectures for Tech Ops IT. Translates business requirements into technical solutions, supports data modeling and warehouse integration, establishes standards for BI and advanced analytics, ensures data quality and integrity, coordinates warehouse changes with reporting teams, and recommends technology and process improvements.

Designs and leads enterprise database architectures, data models, integrations, governance, and performance initiatives. The role supports scalable and secure SQL Server environments, cloud platforms, data warehouses, ETL processes, reporting, analytics, and transportation safety data systems. Responsibilities include optimization, security, backup and recovery, documentation, technical standards, and collaboration with software engineering and business teams. The position requires strong relational database, SQL development, administration, and enterprise data modeling expertise.

Lead data strategy and execution for emerging sectors, transforming large consumer datasets into accurate, scalable client insights. Responsibilities include resolving data-quality issues, designing workflows, maintaining sector taxonomies, partnering with product, revenue, engineering, and insights teams, and coaching analysts. The role requires hands-on analysis, production-grade data workflow development, stakeholder communication, and ownership of quality standards and methodologies in a rapidly evolving environment.