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Staff Analytics Engineer
Buenos Aires, Argentina (Hybrid)
Job Overview
Our client is a mission-driven, general technology platform focused on connecting individuals, communities, and organizations in meaningful ways.
The platform operates at scale, enabling data-driven decision-making, real-time insights, and innovative digital experiences.
We are seeking a Staff Analytics Engineer to join a high-impact Data team responsible for building and scaling the organization's modern analytics layer.
This role sits at the intersection of data engineering, analytics, and product, and is critical in transforming raw data into trusted, well-modeled, and accessible datasets.
You will play a key role in enabling self-service analytics, experimentation, and AI-driven insights, partnering closely with stakeholders across engineering, product, analytics, and data science to drive business growth and operational excellence.
This is a hybrid role based in Buenos Aires, Argentina.
The Role
Design, build, and maintain scalable data models that power analytics, reporting, and experimentation
Develop and manage data transformation workflows using dbt or similar tools, following modern ELT best practices
Define and maintain a metrics layer / semantic layer to ensure consistent and trusted business definitions
Build curated, analytics-ready datasets from multiple sources including event data, transactional systems, and third-party APIs
Partner with stakeholders to translate business questions into well-defined metrics and data models
Ensure data quality and reliability through testing, validation, and monitoring frameworks
Optimize query performance and cost efficiency within modern cloud data warehouses (e.g., Snowflake or equivalent)
Enable self-service analytics by designing intuitive, well-documented data models and datasets




Support and scale experimentations frameworks, including A/B testing and metric standardization
Leverage AI-assisted tools (e.g., Claude) and agentic workflows to accelerate data modeling, documentation, and delivery
Contribute to building AI-ready data layers, enabling governed access to trusted datasets for advanced analytics and LLM-driven use cases
Collaborate with data engineers to define data contracts and improve upstream data reliability
Document data models, metrics, and lineage to improve discoverability and trust
Contribute to data governance practices, including naming conventions, versioning, and access controls
Promote and drive adoption of analytics engineering best practices across the organization
Required Qualifications
5+ years of experience in analytics engineering, data engineering, or advanced analytics
Strong expertise in SQL (advanced querying, optimization, window functions)
Hands-on experience with dbt or similar transformation frameworks
Experience working with modern cloud data warehouses such as Snowflake, BigQuery, or Redshift
Strong understanding of data modeling best practices (dimensional modeling, star schema, etc.)
Experience defining and managing business metrics and semantic layers
Familiarity with event-based data models and user behavior tracking
Experience with analytics and BI tools such as Looker, Tableau, Sigma, or similar
Experience using AI-assisted development tools (e.g., Claude,



GitHub Copilot) to accelerate development and documentation
Understanding of how LLMs and agentic workflows interact with semantic data layers
Strong communication skills and ability to work cross-functionally
Preferred Qualifications
Experience with experimentation platforms and A/B testing frameworks
Familiarity with metrics layer tools (e.g., LookML, MetricFlow, Cube, Transform)
Experience with event tracking tools (e.g., Segment, GA, Heap, CDPs)
Experience with Python for data transformation or analysis
Knowledge of data orchestration tools (e.g., Airflow, Prefect)
Experience with data governance and cataloging tools
Familiarity with machine learning data pipelines or feature stores
Experience with Reverse ETL tools (e.g., Hightouch, Census)
Why You'll Love This Opportunity
High Impact: Help shape a modern analytics ecosystem that drives key business decisions at scale
Innovative Environment: Work with cutting-edge tools in a fast-paced, data-driven organization
Collaborative Culture: Partner with talented teams across engineering, product, and data
Growth Opportunities: Expand your expertise in analytics engineering, AI, and modern data platforms
Competitive Compensation & Benefits: Attractive salary and comprehensive benefits package
Flexible Work Model: Hybrid work environment supporting work-life balance
What Sets This Role Apart
This is a unique opportunity to define and scale the analytics layer of a modern data platform, enabling trusted insights, experimentation, and AI-driven innovation.
You will have the chance to influence how data is modeled, consumed, and leveraged across the organization, while working at the forefront of analytics engineering and AI-enabled data workflows.

Postúlate en Kit Empleo: kitempleo.com.ar/empleo/q1jlo

📌 Staff Analytics Engineer (Buenos Aires)
🏢 Visael
📍 Buenos Aires