About the company
We are looking for an experienced Lead Analytics Engineer to provide technical leadership and shape the organization's analytics engineering strategy. You will design and maintain a reliable, scalable single source of truth that empowers business teams to make informed, data-driven decisions.
Responsibilities
- Data modeling and single source of truth: Design, build, and maintain clean, tested, and well-transformed data models within the data warehouse using dbt or Dataform
- Semantic layer and self-service analytics: Develop and maintain semantic layers and data catalogs, enabling Business Analysts to create dashboards and operational analyses efficiently
- AI-ready data context: Enrich schemas, metadata, and repository documentation to provide context for AI-powered coding tools, including Claude Code and Copilots
- Data quality and observability: Establish and implement testing frameworks, including dbt tests, monitoring alerts, and observability practices
- Technical leadership: Define and promote development standards, DataOps practices, pull request reviews, and version control workflows. Mentor and support other Analytics Engineers
- Cross-functional collaboration: Partner with Data Platform and Engineering teams to integrate data pipelines, establish data contracts, and ensure reliable data flows
- Continuous improvement: Identify opportunities to strengthen analytics engineering processes, improve documentation, and make data assets more accessible
Requirements
- At least 6 years of experience working in data environments, including a minimum of 3 years specializing in Analytics Engineering
- At least 2 years of experience leading Analytics Engineering teams or specialized engineering groups
- Advanced SQL skills and strong hands-on experience with dbt or Dataform in cloud data warehouse environments
- Experience with one or more platforms such as Google Cloud Platform (GCP) BigQuery, Snowflake, or Amazon Redshift
- Practical experience with analytical data modeling methodologies, including Kimball, Star Schema, and Data Vault
- Proficiency with Git and version control, experience implementing CI/CD workflows for data through DataOps, and intermediate Python knowledge
- Experience implementing and maintaining data catalogs and documentation solutions such as DataHub, Atlan, or dbt Docs, as well as developing and maintaining semantic layers
- Ability to translate complex business requirements into scalable, reliable technical data models
- Strong interpersonal skills, with the ability to work effectively across technical and business teams
- Demonstrated ability to guide other engineers, establish technical standards, provide constructive feedback
- The role is advertised as fully remote across Latin America
Conditions
- Fully remote work within Latin America
- Purpose-driven work: Contribute to a financial inclusion mission focused on expanding access to credit
- Trust-based culture: Work in an environment that emphasizes intentional decision-making, transparency, and accountability
- Creativity and curiosity: Bring forward new ideas, explore innovative approaches, and contribute to continuous improvement
- Inclusive collaboration: Participate in a culture that values every team member's voice
- Impact-focused environment: Help build reliable data foundations that support better business decisions