Top Data Analyst Jobs in Mexico City

Executes enterprise data strategy by designing, building, and maintaining scalable data pipelines, curated data layers, governance frameworks, and analytics-ready data products. Translates business requirements into reliable, compliant technical solutions, supports data quality and automation, collaborates with analytics and business teams, and mentors junior team members.

The CIAM Business Analyst gathers and prioritizes customer identity requirements, translating business needs into epics, features, user stories, acceptance criteria, and process flows. The role partners with product, security, architecture, engineering, UX, and digital teams to improve registration, authentication, authorization, identity lifecycle, and account recovery experiences. Responsibilities include backlog management, Agile ceremonies, customer journey analysis, UAT support, requirements validation, risk and dependency tracking, and continuous improvement of CIAM capabilities across digital channels.

Lead a multidisciplinary analytics team across chat, conversion, retention, AI, and operations. Develop KPI frameworks, dashboards, funnel and lifecycle analyses, experimentation strategies, and actionable product recommendations. Manage and mentor data professionals, establish the analytics roadmap, investigate ambiguous business problems, and partner with Product, Operations, AI, Growth, and leadership to improve conversion, retention, customer experience, and operational efficiency.

Leads a multidisciplinary analytics team across chat, retention, AI, and operations. Owns KPI frameworks, funnels, retention analysis, dashboards, experimentation, and operational analytics. Partners with Product, Operations, AI, Growth, and leadership to identify business drivers, improve conversion and retention, increase efficiency, and turn ambiguous questions into actionable recommendations. The role combines hands-on analysis with team leadership and stakeholder management.

Develops and maintains forecasting models for clinical site payments, integrating Medidata Payments data and supporting financial reporting. Analyzes plan-versus-actual performance, budget variances, and forecast risks; prepares client-ready reports and reconciliations. Partners with Revenue Recognition, Clinical Operations, Project Analysis, and planning teams to support audits, change orders, study closeouts, compliance, and sponsor reporting requirements.

Own the growth experimentation program, including test design, power calculations, statistical rigor, readouts, and anytime-valid monitoring. Build a trusted acquisition-to-conversion funnel across paid, organic, and partner channels, incorporating CAC, LTV, and conversion metrics. Extend self-serve experimentation tooling in Lightdash and Python, improve instrumentation with Segment and Flagsmith, automate routine analysis, and influence Growth PM and marketing decisions through clear, statistically sound insights.

Lead Product Data Analyst responsible for marketplace modeling, advanced SQL analysis, A/B testing, reporting, dashboard development, metrics governance, and dbt-powered data modeling. The role partners with product managers and stakeholders to turn analysis into business decisions, improve data self-service, document trusted metrics, and nurture a data-driven culture. It is a fully remote individual-contributor position focused on the Pro supply side of the marketplace.

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.

Govern customer master data across ERP, CRM, and MDM systems; process service requests, resolve duplicates, validate records, perform data quality remediation, support compliance controls, maintain documentation, report on KPIs and SLAs, and assist with governance initiatives and system testing. Mentor junior coordinators and collaborate cross-functionally to resolve issues affecting customer onboarding and order-to-cash processes.

Researches and validates corporate actions such as rights offerings, splits, and dividends; monitors global news sources; inputs and audits data in proprietary databases; maintains data governance and quality standards; resolves client queries; coordinates with global teams and technology partners; and supports index calculations, projects, documentation, and workflow improvements.

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.

Defines and certifies HR metrics and data assets across Workday, Dayforce, and PeopleSoft. Translates Power BI requirements into metric definitions, business rules, data mappings, validation criteria, test cases, and acceptance criteria. Partners with HRIS, HR, analytics, and engineering stakeholders to reconcile data, resolve definition conflicts, manage sign-off, support UAT and defect triage, and maintain documentation for trusted workforce analytics.

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.

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.

Investigate and resolve streaming catalog, feed, data, and process issues using Python, APIs, logs, and technical workflows. Identify root causes, troubleshoot independently, escalate complex problems with clear diagnoses, and communicate findings to technical teams and clients. Use AI tools and prompting to support analysis, document solutions, manage multiple investigations, and improve recurring workflows while meeting deadlines and SLA requirements.

Early-career Data Engineering Analyst supporting AIG’s Data Office through a rotational program. Responsibilities include developing cloud-based data pipelines, collecting and transforming data, building modern software systems, and supporting analytics and data science use cases. The role emphasizes data quality, security, compliance, collaboration, analytical problem-solving, and professional development through mentoring, masterclasses, and on-the-job experiences.

Serves as a bridge between procurement stakeholders and technical teams by translating business needs into SAP and data-driven solutions. Analyzes procurement processes, identifies optimization opportunities, and delivers insights through analytics and reporting. Collaborates cross-functionally to improve operational excellence and support informed decision-making.

Conducts risk assessments of clinical trial data, identifies mitigation strategies, monitors data quality and integrity, collaborates on risk management plans, communicates statistical insights, and supports regulatory documentation and audit preparation.

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.

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.

Own newsroom analytics supporting editorial, audience, and product decisions. Develop dashboards, automated reporting, measurement frameworks, deep-dive analyses, and A/B tests. Maintain reporting data quality and pipelines in partnership with engineering and product teams. Translate findings for nontechnical stakeholders, strengthen analytical practices, mentor junior analysts, and drive adoption of insights across the organization.

Write SQL queries, build dashboards and recurring reports, support newsroom analyses and A/B testing, troubleshoot data quality issues, and communicate findings to editorial, audience, and product partners. The role also involves maintaining documentation, collaborating with data engineering, and using AI tools to automate analytical workflows.

Gather and document business and data requirements, create functional specifications and source-to-target mappings, and analyze healthcare payer datasets using SQL and Databricks. Define transformation rules with technical teams, support UAT and data validation, document data lineage and dictionaries, identify data quality issues, and facilitate communication between stakeholders and engineering teams to improve reporting and operational efficiency.

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