Top Data Analyst Jobs in Mexico

Monitor and improve healthcare data file exchanges across clients, vendors, and internal systems. Analyze insurance claims, eligibility, enrollment, and EDI file mappings; troubleshoot data, file movement, and SFTP issues; coordinate EDI testing and implementations; validate data against business requirements; communicate operational status; and improve DataOps workflows, documentation, and processes.

Analyze user behavior, product performance, experiments, and academic research data to guide product decisions and health outcomes. Responsibilities include building Mixpanel dashboards, validating event tracking, querying Snowflake with SQL, developing Python analyses and automation, maintaining data pipelines, creating BI visualizations, conducting user research, performing statistical testing, preparing research manuscripts, and supporting grant-funded projects.

Develops, enhances, tests, debugs, and supports financial-services applications using Java, Ab Initio, data warehousing, microservices, and batch processes. The role analyzes code and vulnerabilities, consults with users and technology teams, resolves application issues, recommends programming solutions, and supports systems across L1-L3 levels. It operates with limited supervision, advises junior analysts, manages risks and compliance responsibilities, and contributes to application development initiatives.

Build and maintain Domo dashboards, reports, dataflows, and ETL processes; integrate legal case management data; validate data quality; translate operational workflows into reporting structures; identify trends; and present actionable insights to law firm clients. The role also includes requirements gathering, documentation, client support, and explaining data to nontechnical stakeholders while managing multiple priorities independently.

Build and maintain Power BI dashboards and reports, develop Python data transformation scripts, and support Azure Data Factory pipelines. Query and optimize Azure SQL databases, apply dimensional modeling and data warehousing principles, document data logic, resolve data quality issues, and translate business requirements into reliable reporting solutions for technical and non-technical stakeholders.

Analyzes panel operations data, monitors performance and risks, validates pipelines, builds dashboards and predictive models, automates workflows with AI, and drives continuous improvement. The role creates action plans, troubleshoots operational issues, supports audit readiness, and collaborates with Operations, Technology, Quality, and Workforce Management teams. Strong SQL, Excel, Python, AI-tool, and data visualization skills are required, along with English-Spanish bilingual communication.

The Senior Data Analyst will drive performance monitoring and decision-making through actionable insights, complex data analysis, and visualization. Responsibilities include KPI identification, dashboard creation, and training for data-savvy users.

Extracts, cleans, validates, and analyzes complex structured and unstructured datasets using SQL, Excel, Python, or R. Builds dashboards, visualizations, reports, and presentations with tools such as Power BI and Tableau. Translates analytical findings into actionable insights, supports data governance and ETL activities, documents methodologies, and collaborates with international analyst, research, data, and client-facing teams. The role also uses AI tools and automation to improve research, analysis, and reporting workflows.

Leads ingestion, review, reconciliation, and quality control of portfolio company and asset-level data from private markets general partners. Coordinates metric collection, validates financial and operating data, uses AI extraction tools to improve scalable processing, and ensures accurate reporting in internal systems. The role manages deadlines, escalates data issues, communicates with general partners and cross-functional teams, and may mentor junior analysts while contributing to operational improvements and team leadership.

Build and maintain BI dashboards, reporting tools, and automated data workflows. Analyze customer behavior, funnels, retention, engagement, and product adoption to deliver actionable insights across Product, Operations, Marketing, Finance, and Leadership. Use AI tools and APIs to improve analytics workflows, self-service exploration, data-quality checks, and insight generation while validating accuracy, privacy, and business impact.

Lead paid media analytics for Life Company, using SQL/Python and advanced statistics to measure and optimize paid social/search and AI-powered search. Build audience segmentation, run incrementality/experimentation, create visualizations and recommendations, and partner with marketing to drive acquisition and engagement.

Monitor transactions and customer accounts for suspicious activity, investigate suspected fraud, analyze large datasets with SQL and Python, identify fraud patterns, document findings, and develop prevention rules and controls. The role also requires staying current on emerging fraud threats, using fraud detection tools, and leveraging Claude or equivalent large language models to improve productivity, research, and communication.

Own Trailhead’s content analytics, learner satisfaction measurement, and business impact analysis. Build semantic models, data pipelines, dashboards, cohort and propensity methodologies, predictive frameworks, and qualitative text-analysis workflows. Connect learner engagement, survey feedback, content performance, and Salesforce commercial outcomes. Lead Tableau and analytics platform strategy, make data agent-queryable, and communicate high-confidence insights to content, marketing, product, sales, customer success, and executive stakeholders.

Develop and maintain Power BI analytics solutions focused on supply chain, business, and finance. Convert legacy reports, transform and model data, perform statistical analysis, manage end-to-end data processing, validate data accuracy, and collaborate with business stakeholders. The role requires building data structures, supporting predictive forecasting, and working with SQL Server, ETL, SSRS, SSIS, SSAS, Snowflake, DAX, and Power Query in Agile delivery teams.

Lead a multidisciplinary analytics team across product, retention, AI, chat, and operations. Own analytics roadmaps, KPI frameworks, dashboards, funnel and cohort analysis, retention strategy, conversational metrics, and operational performance measurement. Translate ambiguous business questions into actionable insights, product recommendations, experiments, and measurable outcomes. Partner with Product, Operations, Growth, AI, Customer Experience, and leadership while developing analytical talent and improving data-driven decision-making.

Manages supplier master data across ERP, procurement, and workflow systems. Responsibilities include supplier onboarding, maintenance, banking and tax updates, data validation, duplicate analysis, audits, cleansing, compliance reviews, issue resolution, reporting, stakeholder support, training, UAT, and process improvement. The role supports Procure-to-Pay operations, supplier lifecycle governance, automation, internal controls, and audit requests while collaborating with Procurement, Accounts Payable, Compliance, Tax, Treasury, and global teams.

Support HR Data Lake expansion through data discovery, mapping, validation, governance, quality management, and flow analysis. Gather requirements from HR and technical stakeholders, develop reporting and analytics solutions, improve HR processes through automation and redesign, and support HR transformation initiatives. Coordinate cross-functional projects, document processes and data definitions, monitor implementation risks, and partner with HRIS teams on Workday and broader HR technology programs.

Designs and maintains Power BI dashboards and reports, develops Python data transformation scripts, and supports Azure Data Factory pipelines and Azure SQL databases. Applies data warehousing and dimensional modeling principles, translates business needs into reporting solutions, documents data logic, resolves data quality issues, and follows governance requirements while communicating findings to nontechnical stakeholders.

We are seeking a Data Analyst with strong Domo experience to build dashboards, manage data flows, and provide actionable insights for clients, primarily law firms.

Manage and govern supplier master data across ERP and procurement systems. Process onboarding, updates, banking/tax changes, perform data quality reviews, audits, duplicate analysis, and root-cause investigations. Support stakeholders, enablement, reporting, UAT, audits, and continuous improvement/automation initiatives to ensure compliance and data integrity.

Oversee credit operations, including investigations, scoring, credit limits, periodic reviews, and customer master data accuracy. Partner with Sales and Customer Service to resolve credit holds, onboarding issues, and customer setup challenges. Maintain SOX, internal control, and order-to-cash governance compliance. Review credit and master data decisions, support SAP and HighRadius process improvements, and identify opportunities to improve cycle time, data quality, automation, and customer experience.

Lead a multidisciplinary analytics team supporting product, retention, AI, chat, and operations. Own KPI frameworks, conversion funnels, lifecycle and retention analysis, conversational analytics, dashboards, experimentation, and operational performance measurement. Translate ambiguous business problems into actionable insights, product recommendations, and measurable experiments while partnering with Product, Operations, Growth, Fintech, AI, and leadership stakeholders. Establish the analytical roadmap, develop team talent, and improve data-driven decision-making across the organization.

Supports custom research and data consulting projects by sourcing, cleaning, transforming, modeling, validating, documenting, and delivering client-ready datasets and insights. Performs quality checks, applies data methodologies, manages delivery tasks, communicates findings, supports project governance, and collaborates across data, consulting, commercial, product, and delivery teams. The role also contributes to feasibility assessments, process improvements, and responsible use of AI-enabled data approaches.

Analyzes human-generated data quality across AI programs using SQL, Python, statistical methods, and hands-on annotation review. Investigates quality issues, identifies failure patterns, measures impact, and develops recommendations. Supports quality pipelines, automated validations, rubrics, gold sets, calibration exercises, reporting, and dashboards. Collaborates with quality engineering, operations, delivery, and engineering teams to improve annotation design, training, tooling, and quality controls.

Analyze and optimize a two-sided healthcare marketplace through health metrics, root-cause analysis, cohort modeling, dashboards, and decision-support analytics. Partner with Demand, Supply, Operations, Product, Data Engineering, and Data Science leaders to guide capacity planning, provider onboarding, market expansion, and operational strategy. Build scalable analytics models and reporting infrastructure while translating complex data into executive recommendations.