Top Senior Data & Analytics Jobs

Supports quantitative investment research across equities, fixed income, and managed products. Analyzes performance, risk, peer groups, and market data; develops dashboards, datasets, reporting tools, validation controls, and automated processes. Partners with research teams to resolve data issues, communicate findings, improve analytical efficiency, and support investment due diligence. Requires a Series 7 license or the ability to obtain one within 120 days.

Manage national health monitoring and surveillance platforms and studies, coordinating stakeholders and vendors to ensure high-quality data collection. Analyze diverse data sources, generate insights, develop recommendations for policy and strategy, and communicate findings through visualization and presentations. Lead cross-functional collaboration and contribute to reviews of health promotion strategies.

Build and maintain scalable data pipelines from financial data vendors into Snowflake and Databricks gold tables supporting machine learning. Lead end-to-end projects involving LLMs, RAG, and AI technologies; implement CI/CD, infrastructure-as-code, containerization, testing, monitoring, and cloud-native deployments. Collaborate with stakeholders, ensure data quality, mentor junior engineers, and travel up to 20% to support distributed teams.

The Senior Data Analyst translates commercial business needs into technical data specifications, writes complex SQL queries, extracts and validates large datasets, and automates workflows with Python. The role delivers accurate analytics and reporting, communicates findings to technical and non-technical stakeholders, supports pre-sales and RFP activities, manages competing requests, and collaborates with Operations, Strategy, and Data Engineering teams.

Designs and delivers Finance BI dashboards, data models, reports, and self-service analytics. Translates Finance requirements into technical specifications, investigates data discrepancies across SAP and other enterprise systems, performs SQL-based reconciliation and root-cause analysis, and improves reporting performance and reliability. Leads testing, governance, controls, and stakeholder sign-off while evaluating automation and AI-assisted analytics opportunities.

Own MISUMI’s Snowflake data platform, dbt project, and ELT pipelines. Administer security, access, performance, and cost controls; build trusted dimensional models; resolve pipeline and data-quality issues; manage GitHub workflows; translate business needs into data solutions; and promote disciplined AI-assisted engineering practices. Mentor analysts and engineers, lead technical reviews, maintain documentation and QMS processes, and support regulated data environments.

Own end-to-end data domains, designing and maintaining curated analytics models across supply chain, finance, and syndicated data. Lead dimensional modeling, data quality, SLAs, incident response, Redshift cost optimization, and migrations from spreadsheets to governed models. Resolve metric definitions, document technical decisions, partner with Data Engineering, shape backlogs, mentor analysts and engineers, conduct code reviews, and participate in hiring.

Designs and maintains scalable analytics data models, pipelines, warehouses, governance processes, data quality checks, and reporting infrastructure. Partners with engineering, product, and business stakeholders to define metrics, improve data integrity, develop dashboards, enable self-serve analytics, and train users on data tools. The role also supports PermitFlow’s data stack and uses LLMs to enhance analytics workflows.

Designs and maintains secure, scalable Microsoft Fabric data pipelines, Lakehouses, warehouses, and infrastructure. Implements encryption, access controls, governance, compliance, monitoring, CI/CD, infrastructure-as-code, containerization, and automated security testing. Collaborates with security, platform, data science, and engineering teams to improve data reliability and operational excellence. Requires strong SQL, data engineering, Azure, DevOps, and data security experience, along with US citizenship.

Analyzes constellation capacity, customer demand, product usage, revenue, pricing, and operational performance. Maintains and improves Python- and SQL-based workflows and business intelligence datasets, develops quantitative analyses for Product and Sales teams, and translates complex data into actionable recommendations for technical and non-technical stakeholders.