Top Data & Analytics Jobs

Supports internal and external clients using Virtu’s analytics products, analyzes trade data, develops actionable recommendations, delivers client presentations, contributes to sales and product initiatives, and improves operations through data, technology, and automation.

Analyze telematics, IoT, sensor, and firmware data to evaluate hardware performance, reliability, and field issues. Build dashboards and reports, identify trends and anomalies, apply statistical and machine learning techniques, validate firmware improvements, and provide actionable insights to engineering, product, data science, and customer support teams. Help develop scalable data pipelines and promote data-driven hardware and software development.

Own Modal’s go-to-market data platform, including organization and people graphs, identity resolution, CRM schemas, Snowflake and dbt models, reverse ETL pipelines, revenue operations metrics, forecasting, attribution, and data quality systems. Partner with Data, RevOps, and Marketing to support customer context, routing, territory management, campaigns, reporting, and reliable GTM workflows.

Manages the organization’s data engineering, database, Salesforce, reporting, and systems administration functions. Maintains data pipelines, integrations, databases, dashboards, and recurring reports; troubleshoots data quality and system issues; supports data governance, documentation, privacy, and compliance. The role also trains staff, translates technical requirements for stakeholders, and advances technology adoption, reporting automation, performance measurement, and responsible AI practices.

The Data Architect will define enterprise data architecture standards and design scalable, secure Azure-based data platforms. Responsibilities include data modeling, semantic layer design, governance, metadata and security architecture, AI-ready data foundations, platform modernization, vendor and business engagement, architecture documentation, and operational processes. The role also guides CI/CD, Infrastructure as Code, automation, prototyping, and engineering best practices while influencing enterprise-wide transformation initiatives.

Designs, builds, automates, and maintains marketing data pipelines, integrations, models, and databases. The role ingests and transforms data from advertising and marketing platforms, ensures data quality, supports analytics and reporting, and monitors pipeline performance. Responsibilities include API integrations, documentation, troubleshooting, stakeholder collaboration, automation, and applying AI and LLM tools to improve data engineering workflows.

Own end-to-end market research engagements, including research design, discussion guides, qualitative and quantitative analysis, insight synthesis, presentations, and strategic recommendations. Partner with enterprise insights, marketing, and product leaders, leverage AI-powered research tools, build customer relationships, develop scalable methodologies, and collaborate with Sales, Customer Success, and Product to shape Strella’s research offering.

Leads performance measurement, KPI development, reporting, and data-driven decision support for federal programs. Analyzes data from databases, APIs, files, and Amazon S3 using Python and SQL; develops validation methods, dashboards, reports, and analytical narratives. Partners with engineering, product, UX, delivery, and government stakeholders; evaluates generative AI outputs; establishes data quality standards; mentors colleagues; and translates ambiguous client needs into practical recommendations.

Build a canonical entity and knowledge graph for identity resolution, permissions, compliance, and agent authorization. Develop production data pipelines across internal systems, graph-based correlation, ML matching, schemas, APIs, provenance, bitemporal models, drift detection, and delegation credentials. Partner with Finance and Compliance on classification pilots while enforcing privacy, regulatory compliance, jurisdictional partitioning, and auditability.

Owns the strategic direction, prioritization, and governance of an enterprise data domain. Coordinates Data Stewards, Data Custodians, business leaders, and enterprise data product teams to improve data quality, accessibility, compliance, alignment, and adoption. Leads domain working groups, prioritizes data issues and products, aligns cross-domain initiatives, translates business needs into data specifications, and escalates conflicts when necessary.