Top Data & Analytics Jobs

The Data Analyst gathers, validates, and analyzes data from multiple sources to identify trends, evaluate KPIs, and generate actionable insights. They develop and maintain reports, dashboards, visualizations, and business intelligence solutions using tools such as Power BI. The role also involves partnering with stakeholders, translating business needs into analytical requirements, presenting findings to technical and non-technical audiences, documenting work, and improving reporting and analytical processes.

Designs and maintains Power BI dashboards and reports for sales decision-making. Extracts, integrates, cleans, and analyzes data from multiple market and category management sources. Conducts line reviews and category performance analyses, identifies trends and growth opportunities, and delivers data-driven recommendations. Develops customized dashboards, reporting materials, and PDF documentation to support sales teams, product evaluations, and customer presentations.

Collect, clean, transform, analyze, and maintain fund and CRM data related to venture and growth equity. Ensure data quality, manage databases and taxonomies, conduct statistical analysis, create dashboards and reports, and track market and competitive activity. Partner with attorneys and cross-functional teams to deliver insights supporting fund practice decisions and business development.

Analyzes autonomous-vehicle data and driving scenarios to validate dataset quality, identify edge cases and coverage gaps, monitor quality metrics, and investigate anomalies. Reviews annotation batches, maintains dashboards and reports, and automates validation and testing workflows using Python, Pandas, and ClickHouse. Collaborates with product and engineering teams to improve annotation efficiency, testing processes, and data quality.

Build and maintain scalable production data pipelines, infrastructure, warehouse models, analytics platforms, and data-quality systems. Partner with software engineers to instrument product features and ensure reliable event data. Support Hex and Snowflake self-serve analytics, maintain business metrics and data logic, and develop monitoring, validation, alerting, and observability tooling. The role also collaborates with product, analytics, marketing, and engineering teams, with potential future exposure to recommendation and LLM-based product work.

Designs and leads scalable real-time and batch data pipelines, data platforms, architectures, data products, and intelligent APIs. Ensures data quality, supports BI and AI/ML initiatives, and develops ingestion, processing, migration, and analytical solutions for big data, NoSQL, and data warehouse environments. Provides technical leadership, mentorship, code reviews, testing, CI/CD implementation, system monitoring, troubleshooting, and cross-functional translation of business requirements into reliable cloud-based solutions.

Own marketing measurement models for multiple customers, from configuration and QA through interpretation, updates, escalations, and action planning. Partner with strategy managers to translate causal MMM results into budgeting and channel decisions, protect revenue through high-quality deliverables, build scalable playbooks, supervise AI workflows, and provide customer feedback to product, science, and engineering teams.

Designs and evolves enterprise data architecture across master data governance, MDM, data warehousing, and analytics. The role establishes governance policies, stewardship models, data quality metrics, golden-record strategies, integration patterns, data lineage, and warehouse models. It supports SQL Server and Microsoft Fabric platforms, integrates ERP, CPQ, CRM, and other business systems, advises on tooling and architecture decisions, and collaborates with business and technical stakeholders across a multi-site manufacturing organization.

Leads the reliability, quality, scalability, and operational support of cloud-based data platforms and pipelines on GCP. Responsibilities include managing batch and streaming workloads, SLAs and SLOs, data quality monitoring, incident response, recovery processes, infrastructure as code, automation, orchestration, CI/CD, governance, and runbooks. The role provides technical leadership, mentors engineers, and collaborates with data engineering, SRE, platform, analytics, and business teams.

Build and maintain scalable data infrastructure, pipelines, warehouses, and models on cloud platforms, primarily GCP. Develop batch and real-time ETL/ELT workflows using Python, SQL, and Airflow-based tools; implement data quality, governance, metadata, lineage, CI/CD, and automation. Support production machine learning environments, optimize pipeline performance, collaborate with architects and analytics teams, lead solution delivery, and mentor data engineers.