Top Data Analyst Jobs in Leon

Partner with cross-functional teams to define metrics, write SQL, build dashboards, run exploratory analyses, and create Python-based analytics workflows. Deliver scalable reporting, root-cause analyses, and insights using visualization tools and modern AI assistants to drive business decisions and operational improvements.

Manage tracking plans and data governance for customer and product analytics. Build Mixpanel dashboards, translate business needs into technical requirements, validate data quality, consult stakeholders, and support data integration across data-marts and warehouses. Liaise between IT and Product, troubleshoot data issues, and continuously improve analytics platforms and documentation.

Build and maintain data models, dashboards, reports, and dbt models supporting cross-functional decision-making. Process large datasets, establish reporting sources of truth, bridge technical and business teams, and document knowledge bases and business definitions for internal AI systems. The role also involves identifying cost-saving opportunities, communicating with stakeholders, and using AI to develop solutions and fix bugs.

Provide data analysis and reporting as a virtual assistant: create and maintain reports, perform data entry and validation, generate visual insights, collaborate with stakeholders, track action items, and improve workflows to optimize reporting efficiency.

The Revenue Operations Data Analyst will analyze datasets, optimize dashboards, and develop data pipelines to support revenue operations and strategic decision-making.

Lead analytics strategy for global performance marketing by analyzing paid media, digital advertising, and campaign performance. Deliver executive reporting, ROI and incrementality analyses, experimentation, SEM payback modeling, and actionable recommendations for resource allocation and growth. Connect marketing activity with Salesforce sales pipeline data and collaborate with Marketing, Growth, Product, Sales, and Customer Success leaders to influence strategy and improve acquisition, engagement, and retention.

The Senior Associate Decision Scientist role involves providing analytics support by building reports and dashboards, writing SQL, and maintaining data models while collaborating with stakeholders to derive insights.

Analyzes structured and unstructured datasets using statistical modeling, exploratory analysis, forecasting, SQL, Excel, and visualization tools. Creates complex reports, dashboards, metrics, and demand forecasts; identifies trends, gaps, and automation opportunities; validates data quality; troubleshoots database issues; and supports data infrastructure and reporting improvements.

Own end-to-end product analytics for the Pro team: build production-grade pipelines and dbt models, define north-star metrics, design A/B tests and causal inference frameworks, create dashboards and metric frameworks, embed AI tooling, and translate insights into product recommendations for leadership.

Senior data analyst responsible for statistical modeling, EDA, forecasting, building complex reports and visualizations, assembling large datasets, troubleshooting data issues, performing QA, and improving data systems and forecasting techniques.

Integrate and validate marketing data from multiple sources, ensure accurate campaign tracking and attribution, analyze paid media performance, support A/B testing, build scalable dashboards and pipelines, and partner with marketing and product teams to define KPIs and recommend optimizations.

The Data Analyst role focuses on leveraging advanced analytics to address strategic business challenges, including designing and implementing analytical solutions.

Hybrid finance-data role owning financial data accuracy, infrastructure, and reporting. Maintain and QA Preset/Databricks outputs, build recurring revenue and margin reports, track KPIs and COGS, support budgeting, forecasting, variance analysis, and rolling forecasts to enable faster data-driven decisions.

Analyze chargeback and transaction data to uncover trends, optimize dispute strategies, build dashboards, ensure metric integrity, support product launches, and collaborate cross-functionally to reduce losses and improve dispute outcomes.

Design and maintain dashboards and reports, perform deep-dive analyses to identify trends and anomalies, ensure data integrity with engineers and data scientists, automate reporting, and translate complex datasets into clear insights for non-technical stakeholders.

Partner with Marketing, Sales, Finance, Product and other teams to turn business questions into actionable analysis. Own end-to-end analytics: build datasets and dashboards (dbt, LookML), maintain metric definitions and caveats, use and curate agent tooling for trustworthy answers, and contribute small data platform and pipeline improvements.

Design, develop, and maintain management and executive reporting and dashboards to support Finance and Distribution. Perform data validation, quality assurance, and analysis of large datasets to identify trends, risks, and opportunities. Support advanced analytics projects, translate findings into actionable business insights, and collaborate with stakeholders to define reporting requirements and priorities.

The Senior Data Analyst analyzes large datasets, develops SQL queries, utilizes Python for analytics, and collaborates on insights within GCP and BigQuery.

Analyze digital marketing campaign performance, investigate product and business issues, identify growth opportunities, and develop optimization strategies. The role requires working with enterprise datasets, analytical tools, automation, predictive analysis, segmentation, and visualization to deliver actionable insights and communicate data-driven recommendations to stakeholders and media partners.

Analyze digital marketing campaign performance, develop deep understanding of data sources and analytics tools, automate processes, identify growth opportunities, communicate insights, and deliver actionable optimization plans.

Collect, prepare, validate, and report statistical data for property and casualty insurance. Develop and maintain reports and analytic tools, support metadata and data dictionary upkeep, and coordinate with actuaries, product managers, regulatory affairs, finance, and IT to meet reporting requirements.

The role involves developing predictive analytics models using Python, creating reports, conducting data evaluation, and communicating insights to support business decisions.

Lead and own client-specific QA programs for generative AI data: set QA strategies, run root-cause analyses and CAPA, plan rater training and certification, maintain dashboards, manage escalations, standardize SOPs, pilot automations, coach raters, and ensure secure data handling across distributed teams.

Gather and document requirements for SAP SuccessFactors talent projects, design and support data integration (ETL/API), produce process maps and test plans, liaise between business and technical teams, support change management, and identify/mitigate integration and project risks.

Build, maintain, and optimize data pipelines and ETL integrations (BigQuery, Fivetran, dbt). Design automations (n8n/Zapier/Make), ensure data quality and system reliability, document workflows, troubleshoot pipeline issues, and translate business needs into scalable systems to eliminate manual work.