Top Data & Analytics Jobs

Analyze structured and unstructured data to produce actionable insights for a lending business vertical. Manage daily performance metrics, build analytical models and frameworks, recommend strategies, track initiative financial impact, and collaborate with Marketing, Sales, and Product. Use SQL, Python/R, Tableau and Snowflake to monitor full-funnel performance and drive revenue optimization.

Build, automate, monitor, and optimize batch and streaming data pipelines across cloud platforms and Snowflake. Responsibilities include troubleshooting failures, conducting root-cause analyses, orchestrating ETL/ELT workflows, managing connectors, implementing observability and data-quality controls, optimizing performance and costs, enforcing access controls, documenting procedures, and providing rotational on-call support. The role partners with product, analytics, platform, and architecture teams to deliver reliable enterprise data services.

Designs and implements Hightouch Identity Resolution solutions for enterprise customers. Assesses data architectures, develops identity rules and data models, debugs customer issues using SQL and server logs, explains system behavior, and identifies product gaps. Partners with sales engineering, support, and technical account management while advising technical and executive stakeholders on data strategy and identity architecture.

Own and scale Collective’s data platform by building reliable batch and event-driven pipelines into BigQuery, modeling data with dbt, and enforcing quality, observability, security, and cost standards. Partner with engineers, analysts, and business stakeholders to deliver trustworthy datasets, metrics, reporting, and AI-enabled warehouse access. The role includes production ownership, incident response, governance, infrastructure practices, and support for analytics and LLM-based tools.

Build and maintain finance data pipelines, warehouse models, dashboards, and automations for unit economics, technology budgeting, burn, runway, margins, deal desk, and sales compensation. Develop internal tools and LLM-based agents that help non-engineers access trusted financial data. Partner with finance, sales, and engineering leadership to reconcile discrepancies and improve revenue, cost, billing, payroll, cloud-spend, and accounting workflows.

Lead and manage a team building and operating enterprise data pipelines, warehousing, and integration solutions. Oversee data architecture, ETL, data quality, governance, BI support, vendor selection, and cross-functional collaboration to ensure reliable, scalable, and secure data for business reporting and decision-making.

Leads BI, analytics, and AI initiatives that transform energy market and customer data into dashboards, automated insights, predictive analyses, and strategic recommendations. The role supports pricing, acquisition, retention, marketing, finance, and customer experience decisions through Python, SQL, Tableau, Power BI, generative BI, experimentation, and machine learning. Responsibilities include building executive reporting, evaluating AI-enhanced BI platforms, analyzing customer lifecycle performance, mentoring analysts, and partnering with cross-functional business and technical teams.

Supports the Business Intelligence team by analyzing and visualizing data, cleaning datasets in Snowflake using SQL, maintaining data governance assets, responding to support requests, contributing to analytics projects, and assisting with annual reporting and IRB-related research ethics processes.

Analyzes, cleanses, maps, transforms, reconciles, and validates data throughout enterprise migration projects. Supports ERP implementations, mock loads, testing, cutover planning, production deployments, and troubleshooting. Develops data-quality metrics, mapping specifications, reconciliation reports, and business controls while collaborating with stakeholders, consultants, developers, and project managers. Communicates risks and recommends improvements to data governance and migration procedures.

Leads knowledge engineering and content operations across legal and consulting practices. Partners with subject-matter experts to structure expertise into taxonomies, decision trees, playbooks, metadata standards, workflows, and AI-ready content. Governs content quality, enterprise search, retrieval systems, and experience-management data models while supporting automation, GenAI, ethical-wall compliance, and institutional knowledge reuse. Measures findability, content health, and reuse through reporting dashboards.