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Data Analyst

Discussion

Purpose of the Job
The Data Analyst will be responsible for leading cross-functional reporting and campaign performance data aggregation across all partner and brand initiatives. In this role, you will pull and consolidate metrics from internal manager data exports and partner-facing platforms to build comprehensive post-mortem summaries and automated dashboards. You will be tasked with translating raw execution data into highly polished, executive-ready business reviews that track Return on Investment (ROI) and Service Level Agreement (SLA) compliance. This analytical role requires a detail-oriented professional who can transform complex datasets into clear, actionable commercial insights for leadership teams.
This will be a hybrid position based in company’s and client offices in Mexico City. This role will be required to be in office 2-3 days per week, with the ability to work from home the remaining days.
Key Responsibilities

Aggregate and synthesize performance metrics across disparate partner channels, localized brand campaigns, and external retail footprints.
Extract, clean, and consolidate marketing data utilizing direct data exports from internal managers and self-serve partner-facing platform metrics.
Maintain a centralized performance data repository to ensure consistent, cross-functional visibility into marketing performance and ROI (Return on Investment).
Build comprehensive post-mortem summaries and automated performance dashboards that clearly track key performance indicators (KPIs) against baseline Service Level Agreements (SLAs).
Translate complex, raw execution metrics into polished, presentation-ready business reviews (QBRs) and executive summaries.
Identify historical performance trends and data anomalies, providing actionable data-driven recommendations to help optimization efforts for future partner campaigns.
Maintain, update, and optimize existing operational dashboards across tools like Looker and PowerBI. Ensure underlying semantic layers are performant, query logic is accurate (optimizing LookML and DAX), and parameterized filters provide internal teams with real-time operational telemetry.
Execute responsive, ad-hoc performance queries across using complex SQL (CTEs, window functions, dynamic pivoting) in BigQuery and Snowflake. Utilize Python (Pandas/NumPy) or R (Tidyverse) to wrangle large tabular datasets and isolate statistical anomalies.

Knowledge, Skills + Experience

4–6 years of experience as a Data Analyst, Marketing Analyst, or Business Intelligence Analyst—specifically working with multi-channel marketing campaigns, agency networks, or tech sector accounts.
Bachelor’s degree in Data Analytics, Statistics, Finance, Marketing Analytics, Business Administration, or a related quantitative field.
Native or fluent bilingual proficiency in Spanish and English (written and verbal) to effectively manage regional stakeholders and vendor pools.
Advanced proficiency in SQL (DML/DDL). Highly comfortable extracting and manipulating operational data from cloud-native, distributed data warehouses like BigQuery and Snowflake.
Strong fundamental knowledge of Python or R for tabular data manipulation and local ad-hoc analysis. Hands-on experience reading and debugging Google Apps Script and JavaScript for workspace automation.
Advanced power-user of Google Sheets and Excel, capable of managing dynamic data ingestion, array matrices, and RegEx extractions at scale.
Strong understanding of data types, relational database architecture, and data hygiene best practices. Ability to trace data lineage from front-end UI actions to back-end database tables.

#LI-Hybrid

See also

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