Top Data Analyst Jobs in Mexico City

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.

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.

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.

Builds automated analytics and reporting solutions for FP&A by reverse-engineering Excel processes, querying and reconciling multi-system data, developing dashboards and interactive HTML reports, and exploring AI-assisted workflows. The role performs exploratory and driver-based analysis, improves data pipelines and data marts in partnership with engineering teams, monitors exceptions, translates findings for Finance leaders, and helps establish an AI repository for repeatable FP&A processes.

Analyze complex marketing data, define KPIs and reporting frameworks, govern data quality, build dashboards and models, and deliver actionable insights. The role partners with marketing, product, engineering, and business stakeholders; improves analytics standards and workflows; documents data products; and trains marketing teams to use dashboards and reporting resources effectively.

Gather and document business and data requirements; create functional specifications, source-to-target mappings, data dictionaries, and lineage artifacts. Analyze healthcare payer datasets using Databricks, Databricks SQL Warehouses, Databricks Genie, and complex SQL queries. Support data profiling, reconciliation, validation, UAT, and data quality remediation while collaborating with engineers, architects, stakeholders, and business users.

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.

Build and maintain ETL pipelines and recurring reports for content analytics, learner feedback, and business-impact cohorts. Maintain dashboards/headless analytics, run data quality checks, operate AI query tools, and support stakeholders with data validation and ad hoc requests, following established data architecture and standards.

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.

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.

Analyze and clean data from databases, APIs, and spreadsheets; build dashboards and reports; apply statistical methods, predictive modeling, and A/B testing; and present insights to stakeholders. Gather business requirements, map processes, define technical specifications, support UAT, and liaise between business and technical teams. The role also supports project planning, system improvements, data migrations, workflow automation, and mentoring junior team members.

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 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.

Maintains Salesforce account hierarchies, resolves duplicate account and contact records, validates parent-child relationships, performs OFAC and sanctions screening, and researches account-creation requests. The Analyst documents changes for audit readiness, meets SLAs, reviews AI-flagged findings, escalates risks, and recommends improvements to data-quality processes and automation workflows. This is a hybrid role based in Mexico City.

Maintain Salesforce account hierarchies, investigate duplicate records, validate parent-child relationships, perform OFAC and sanctions screening, and review account creation requests. Document changes for audit readiness, meet service-level agreements, evaluate AI-flagged findings, escalate risks, and recommend improvements to data-quality workflows and automation.

Maintains Salesforce account hierarchies, investigates duplicate records, validates parent-child relationships, performs OFAC and sanctions screening, and reviews account creation requests. The Analyst documents changes for audit readiness, meets SLAs, escalates risks, validates AI-generated findings, and recommends improvements to data-quality workflows and automation.

Maintains Salesforce account hierarchies, researches parent-child relationships, resolves duplicate account and contact records, performs OFAC and sanctions screening, validates account creation requests, and documents changes for audit readiness. The Analyst reviews AI-flagged findings, meets research and creation SLAs, escalates ambiguous or high-risk cases, and recommends improvements to data-quality workflows and automation.

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.

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.