Data Analytics & Insights Specialist

Multiplica Talent

Analytics & Insights Specialist leveraging data to drive marketing decisions and business impact. Collaborating with cross-functional teams on analytics projects in a dynamic environment.

Posted 5/12/2026full-timeRemote • 🇨🇴 ColombiaMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AirflowAmazon RedshiftAWSBigQueryCloudGoogle Cloud PlatformNumpyPandasPythonScikit-LearnSQLTableau

About the role

Key responsibilities & impact

Design and execute advanced analyses on user digital behavior, campaign performance, and conversion funnels to identify patterns, opportunities, and risks.
Generate actionable insights that answer strategic business questions and translate into concrete recommendations for Marketing, Product, and Commercial teams.
Build data storytelling narratives that connect analytical findings to business decisions, tailoring the message to technical, managerial, and executive audiences.
Define KPIs, measurement frameworks, and attribution models that holistically evaluate the performance of the digital ecosystem.
Build and maintain robust data pipelines in BigQuery from sources such as GA4, CRM, media platforms, and transactional databases.
Design efficient, optimized SQL queries on large-scale tables, including Google Analytics 4 export tables (events_*).
Collaborate with Data Engineering teams on data modeling, quality, governance, and availability across GCP and AWS environments.
Design and maintain executive dashboards in Looker Studio (or other BI tools) that deliver clear, timely, and actionable information to stakeholders.
Present findings to C-level audiences, translating complex technical analyses into simple, actionable, business-oriented messages.
Document methodologies, assumptions, and analytical limitations to ensure transparency and reproducibility.
Act as a technical reference within the Analytics & Insights team, supporting junior analysts on best practices in SQL, Python, and modeling.
Collaborate with regional teams across multiple markets, understanding local nuances and consolidating learnings at a regional level.
Promote a data-driven culture, advocating for the responsible use of data and experimentation as a driver of decision-making.

Requirements

What you’ll need

Bachelor's or Master's degree in Statistics, Data Science, Engineering, Economics, Mathematics, Industrial Engineering, or related fields.
Relevant certifications are a plus: Google Analytics, Google Cloud (Data Engineer / Data Analyst), AWS (Data Analytics), or equivalents.
Experience in advanced analytics, data science, or business intelligence roles, preferably in digital, telecommunications, e-commerce, or media industries.
Demonstrated experience leading end-to-end analytics projects: from problem definition to implementation and communication of results.
Experience in regional or multinational environments is a strong plus.
Google Analytics 4 (GA4): configuration, implementation, advanced analysis, and BigQuery export (events_*, intraday tables, event parameters, attribution).
BigQuery / Advanced SQL: designing efficient queries, window functions, partitioning, cost optimization, and integration with GA4 and transactional data.
AWS: hands-on experience with data services such as S3, Athena, Glue, Redshift, or equivalents.
Python: data manipulation (pandas, numpy), visualization (matplotlib, seaborn, plotly), and modeling (scikit-learn, statsmodels).
Machine Learning: command of supervised and unsupervised algorithms (regression, classification, clustering), model validation, performance metrics, and experimentation.
Digital Marketing: deep understanding of the digital ecosystem (paid media, SEO, CRM, CRO, attribution, conversion funnels, customer journey).
Data Visualization: Looker Studio, Power BI, Tableau, or similar tools.
Experience with dbt, Airflow, or other orchestration and analytics modeling tools.
Knowledge of experimentation platforms, CRO tools (Microsoft Clarity, Hotjar, Optimizely), and behavior analytics.
Familiarity with causal inference frameworks (CausalImpact, DiD, propensity scoring).
Experience with generative AI tools applied to analytics and productivity.
Analytical & critical thinking: ability to break down complex problems and draw rigorous conclusions from data.
Insight generation: ability to go beyond the metric and deliver the why and the so-what.
Data storytelling: ability to tell stories with data, structuring clear and persuasive narratives for different audiences.
Business orientation: understanding of the commercial impact of analyses and focus on generating measurable value.
Effective communication: ability to explain technical concepts simply to non-technical audiences.
Autonomy & proactivity: ability to identify analytical opportunities without detailed instructions.
Collaboration: effective work with multidisciplinary, multicultural teams.
English: intermediate to advanced (B1/B2) — able to lead meetings, presentations, and produce technical documentation in English.

Benefits

Comp & perks

Proyecto de 3 meses
Pago por honorarios

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

SQLPythonBigQueryGoogle Analytics 4Machine LearningData VisualizationData ManipulationData ModelingAttribution ModelsKPI Definition

Soft Skills

Analytical ThinkingInsight GenerationData StorytellingEffective CommunicationCollaborationAutonomyProactivityBusiness OrientationLeadershipCritical Thinking

Certifications

Google AnalyticsGoogle Cloud Data EngineerGoogle Cloud Data AnalystAWS Data Analytics