Top Data & Analytics Jobs

Leads the design, administration, optimization, and modernization of enterprise data platforms across SQL Server, Azure, and Microsoft Fabric. Responsibilities include database operations, high availability and disaster recovery, performance tuning, replication, cloud migrations, monitoring, security, governance, and automation. The role collaborates with architects and infrastructure teams, mentors junior engineers, and serves as a subject matter expert for database infrastructure and cloud architecture.

Designs and maintains Power BI reports and dashboards using Microsoft Fabric semantic models. Builds data models, writes and optimizes DAX, applies security controls, validates data quality, and creates certified datasets and reusable templates. Partners with stakeholders to define reporting requirements, presents insights, participates in peer reviews, and uses AI tools to improve analysis and delivery.

Leads the enterprise data management strategy, Data Operations organization, data governance, stewardship, quality, taxonomies, metadata, and master/reference data programs. Partners with engineering, product, business, regulatory, and audit stakeholders to improve data architecture, lineage, controls, lifecycle management, and commercialization of proprietary data assets. Oversees third-party data providers, automation initiatives, operating metrics, change governance, and organizational growth while preparing data for AI, machine learning, semantic search, and advanced analytics.

Leads customer performance analytics for the Growth organization and business units, translating transaction, digital, CRM, and customer data into strategic recommendations. Manages and develops an analytics team, prioritizes high-impact initiatives, establishes data quality and methodology standards, and oversees dashboards, reporting, visualization, and executive storytelling. Partners with senior leaders across Growth, Marketing, Finance, Technology, and CX to identify customer trends, risks, and growth opportunities.

Client Investment Research Analysts support Bridgewater's investment strategies by collaborating with teams to analyze markets, develop insights, and manage research projects, contributing to client service strategies and informing investment decisions.

Processes, analyzes, validates, and manages spatial and tabular environmental data. Creates accurate maps, figures, graphics, web maps, dashboards, and mobile data collection applications for environmental reports, permits, and regulatory submissions. Coordinates GIS data collection with field teams, integrates GPS and remote sensing data, maintains geospatial databases, and collaborates with environmental scientists, engineers, planners, and project managers.

Leads the design and management of scalable cloud database infrastructure across AWS and Azure. Responsibilities include PostgreSQL and SQL Server administration, GraphQL and Hasura API development, cloud migrations, CI/CD automation, infrastructure as code, performance monitoring, security, compliance, data modeling, and mentoring engineers. The role also supports data access layers for AI and application workloads.

Leads analytics and data engineering for Sales and Revenue Operations. Builds reporting in Looker and Snowflake, manages CRM data flows into cloud warehouses, establishes transformation and modeling layers, and develops forecasts, scoring, churn, and expansion models. Supports territory, quota, pricing, and revenue-truth initiatives while presenting insights to finance and company leadership.

Analyze product, user, transactional, and repayment data to develop risk and underwriting models, reduce losses and fraud, monitor model performance, and guide product and growth strategy. Build Looker dashboards and LookML models, conduct segmentation and experimentation, measure CAC and LTV, and communicate actionable insights to product, engineering, marketing, finance, and leadership.

Designs, builds, validates, and maintains governed analytical data models, curated datasets, and reporting layers. Translates business requirements into data mappings, transformation logic, and reusable BI datasets. Develops SQL and dbt tests, performs data reconciliation and root-cause analysis, optimizes Snowflake models, and supports dashboards, reports, UAT, and regulatory extracts. Collaborates with stakeholders, data engineers, architects, analysts, and business teams across insurance and corporate functions.