Top Data Analyst Jobs in Mexico

Lead a team of analysts to analyze large datasets, develop predictive models, create visualizations and reports, ensure data integrity, and provide strategic, sales-focused insights to guide business decisions.

The Data Analyst will manage and update information on ECUs, ensuring technical coherence and compliance with deadlines while coordinating with teams.

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.

Perform complex SQL analyses, build reusable datasets and dashboards, validate data quality, define metrics with stakeholders, and support ML/advanced analytics by preparing datasets and interpreting results.

Analyze customer behavior and product performance using large datasets; build dashboards, reports, and visualizations; develop queries and data models; perform statistical analysis, forecasting, segmentation, and A/B testing; collaborate with cross-functional teams and present actionable insights to stakeholders while improving data quality and analytics processes.

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.

Support business decision-making by gathering, organizing, and interpreting data to identify trends and opportunities. Build data pipelines, dashboards, and reports; modernize manual workflows into scalable, automated systems; apply statistical analysis, cloud platforms, and AI/ML to drive process improvements and operational efficiency while collaborating with stakeholders.

Analyze and transform manufacturing and industrial engineering data into actionable insights using statistical analysis, machine learning, and AI. Build and deploy predictive models, dashboards, and reports; integrate data from enterprise systems; ensure data governance and quality. Support work measurement, standard time, capacity planning, simulation, digital twin initiatives, Industry 4.0 deployments, and collaborate with operations to implement process improvements.

Builds and owns a forecasting model for clinical site payments outside Medidata Payments, links forecasts with Medidata, produces client-ready deliverables, performs plan vs. actual analysis, supports audits, reconciliations, and clinical operations, and ensures compliance with revenue recognition and client requirements.

The Commercial Data Analyst will support revenue optimization and data-driven projects, manage reporting tools, and collaborate with stakeholders to provide actionable insights based on data analysis.

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.

Develop, maintain, and enhance ~50 Project Engineering Power BI reports; connect and validate Snowflake/SAP/PWA data; create new dashboards from user requirements; perform ad-hoc Excel and Power BI analyses; act as reporting SME, review usage, provide training, and deliver data-driven insights to stakeholders.

Supports firm-wide data governance and data quality initiatives. Responsibilities include maintaining core datasets, conducting data quality checks and root-cause analysis, documenting corrective actions, supporting data profiling and migration, maintaining data dictionaries and governance documentation, coordinating organizational structure updates, assisting with UAT, and delivering reports and insights. The role collaborates with data architects, data owners, consumers, and other stakeholders to improve data accuracy and support business decisions.

Supports firm-wide data governance and data quality initiatives by maintaining core datasets, running quality checks, analyzing root causes, documenting remediation, and supporting data management workflows. Collaborates with data architects, owners, consumers, and stakeholders to define requirements, maintain data dictionaries, implement structural changes, support migrations and UAT, and deliver reports and insights. Requires strong analytical, problem-solving, communication, organizational, and relationship-building skills.

Supports the setup, approval, release, and tracking of new part numbers, bills of materials, and engineering change orders. Reviews changes for compliance with engineering and process standards, assigns tasks, coordinates cross-functional troubleshooting, escalates delays, and assists with testing new tools and processes. The role requires collaboration across business units and locations, knowledge of Oracle procedures, and familiarity with PLM and BOM change management.

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.

Lead evaluation of clinical trial data to identify risks and trends, oversee discrepancy analysis, and develop risk mitigation strategies. Partner with cross-functional stakeholders to ensure data governance, quality, and compliance. Provide guidance on best practices and drive improvements in data integrity across studies.

Translate, merge, and transform data from a centralized data warehouse to produce validated, documented reports and extracts. Work with cross-functional teams to deliver BI reports (Tableau/Power BI), enforce data governance, build auditing/validation processes, and provide actionable business insights for stakeholders.

Analyze business performance using SQL, Python, Excel, and BI tools; build data models and KPI tracking solutions; identify growth and efficiency opportunities; support long-term strategy with executive leadership; and communicate insights to cross-functional, nontechnical stakeholders. The role requires independent problem-solving and fluent English and Spanish communication.

Owns the design, development, deployment, and support of Snowflake data models, Streamlit applications, BI reports, and AI-powered data products. Integrates machine learning models, RAG endpoints, and agentic LLM services into reliable user-facing tools. Partners with data scientists, engineers, and go-to-market stakeholders to translate business needs into trustworthy analytics solutions for a B2B SaaS organization.

The Salesforce Data Hygiene Analyst ensures the accuracy and consistency of Salesforce data by resolving quality issues, developing processes, and providing analytics support.

Lead data analysis, BI, and visualization efforts: collect, clean, model, analyze, and visualize large datasets. Build dashboards and reports, apply statistical methods and data mining, ensure data quality/governance, collaborate cross-functionally, and mentor junior analysts while implementing best practices for analytics and reporting.

Work with tower leaders, key users and SMEs to gather and validate process data across sites; perform preload and post-load data QA; resolve defects with cross-functional teams; ensure E2E data quality for tool adoption; validate parameter tuning; understand global template design and deliver plant/network-level information.

Analyze commercial, financial, and operational data to identify trends and insights; build and maintain reports and dashboards; consolidate and validate multi-source data; support forecasting, planning, and ad-hoc analyses; prepare executive presentations and stakeholder materials; improve reporting processes and automation while collaborating with cross-functional global teams.