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.

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.

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.

Collects, organizes, analyzes, validates, and distributes large datasets. Develops and monitors business-focused analytics projects, improves data analysis processes and infrastructure, identifies trends, and generates actionable insights. Designs reporting systems, dashboards, and data views using SQL, Python, AWS Redshift, Tableau, and Power BI. Collaborates with business stakeholders and leaders to support data-driven decisions while applying analytical, organizational, communication, and project management skills.

Develop and maintain MicroStrategy and Logi Analytics reports, dashboards, metrics, datasets, and data visualizations. Write and optimize advanced SQL, validate and reconcile data, analyze BI logic, and work with stakeholders to clarify requirements. Apply relational database, data warehousing, and dimensional modeling knowledge. Use AI-assisted development tools daily, establish responsible AI coding standards, and evaluate LLM-based workflow and automation tooling.

Develop and maintain MicroStrategy and Logi BI reports, dashboards, metrics, datasets, and data visualizations. Analyze business logic, validate and reconcile data, optimize SQL queries, and work with relational databases, data warehouses, and dimensional models. Partner with stakeholders to clarify requirements and solve analytical problems. Use AI-assisted development tools daily, establish responsible AI coding standards, understand LLM fundamentals, and integrate AI into engineering workflows.

Conduct advanced supply chain data analysis, build dashboards and reports using Power BI, OTBI, and SAP BusinessObjects, automate workflows, validate data, and provide actionable insights. Collaborate with cross-functional teams on BI, predictive modeling, statistical analysis, and process improvement initiatives. Mentor entry-level analysts and support stakeholder requirements, reporting optimization, and data-driven decision-making.

Build and maintain Tableau or Power BI dashboards and reports; analyze manufacturing, operational, and financial data; query Snowflake with SQL; support dbt data models; document metrics; and train business users in self-service analytics.

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.

Transform complex data into actionable insights for business and product decisions. Collaborate with Product, Design, Engineering, and cross-functional teams to support a data-driven culture. Build dashboards, conduct predictive modeling, optimize data, and communicate findings clearly using SQL, Python, Tableau, or Power BI.

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.

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.

Analyze and improve data ingestion processes, data quality, reporting standards, and operational performance. Validate loading statistics, cleanse data, resolve inconsistencies, execute testing, track project milestones, document procedures, and coordinate data requirement changes with business, technology, supplier, and client stakeholders. Develop metrics and reports, support reporting entities, and implement data solutions that improve efficiency, reliability, and service quality.

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.

Manage customer and item master data in J.D. Edwards and Oracle ERP systems. Ensure data accuracy, consistency, integrity, and compliance with quality standards. Coordinate cross-functional data setup activities, lead progress meetings, resolve data issues with Product Management, Engineering, Sales, Finance, and Supply Chain, and document data management processes.

Performs data analysis and applies analytical methods to generate recommendations and interpret results. Supports data governance, data risk and controls, data quality, cataloging, lineage, issue management, regulatory alignment, and performance monitoring. Partners across teams, tracks governance metrics and remediation activities, assesses business-process compliance, and provides guidance to colleagues. Requires strong communication, analytical problem-solving, GitHub version control, CI/CD platform familiarity, and 4–8 years of relevant experience.

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.

Drives data collection, analysis, KPI reporting, dashboard development, forecasting, and executive presentations. Builds standardized reporting processes, improves data quality, investigates metric fluctuations, and translates business requirements into actionable insights. Collaborates with cross-functional teams, leadership, vendors, and partners to prioritize information needs, maintain data integrity, automate reporting, and communicate findings effectively.

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.

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.