Senior Analytics Engineer
We are looking for an experienced Senior Analytics Engineer based in Latin America to lead full-cycle data-warehouse and analytics platform implementations for our global clients. This role requires a strong mix of technical expertise, business acumen, and communication skills, as you will work directly with stakeholders across North America, Europe, and Asia.
You will own the entire analytics engineering lifecycle from requirements gathering and data modeling to building ETL/ELT pipelines and delivering high-quality reporting and analytics solutions.
Key Responsibilities:
Data Architecture & ModelingLead end-to-end data-warehouse implementations, including requirements discovery, solution design, development, and deployment.Build and maintain scalable data models (conceptual, logical, and physical) following industry best practices (e.g., Kimball, Data Vault).Translate business needs into clear technical specifications, documentation, and data requirements.Establish and enforce data architecture standards, schemas, and naming conventions.
ETL/ELT Pipeline DevelopmentDesign, develop, and optimize automated ETL/ELT workflows using tools such as Pentaho, TimeXtender, DBT, Azure Data Factory, or similar.Create transformation logic, data-quality validation, and workflow orchestration for complex integrations.Implement robust monitoring, quality checks, and performance optimization across all pipelines.Ensure data accuracy, consistency, and reliability across source and target systems.
Analytics & Reporting EnablementDeliver analytics-ready datasets for BI platforms such as Power BI, Tableau, Looker, or Qlik.Collaborate closely with data analysts, BI developers, and business teams to enable advanced reporting and insights.Optimize data structures for performance, usability, and scalability within reporting environments.
Client Collaboration & LeadershipAct as a technical lead for international client engagements across multiple time zones.Lead requirements workshops, solution walkthroughs, and technical presentations with senior stakeholders.Collaborate with global engineering, analytics, and consulting teams.Mentor junior engineers and contribute to best-practice development across the organization.
Required Qualifications5+ years of experience as an Analytics Engineer, Data Engineer, or Data Warehouse Engineer.Proven experience owning end-to-end data-warehouse implementations.Strong hands-on experience with ETL/ELT tools: Pentaho, TimeXtender, DBT, Azure Data Factory, or similar platforms.Advanced proficiency in SQL and experience with modern cloud data warehouses (SQL Server, Snowflake, BigQuery, Redshift, Azure Synapse, MySQL, PostgreSQL).Expert understanding of data modeling principles and dimensional modeling frameworks.Experience documenting business requirements, technical specifications, data mappings, and process flows.Familiarity with Git-based version control and CI/CD for data pipelines.English proficiency at C1 level (Business Proficient) - capable of leading client meetings, presenting solutions, and writing technical documentation in English.
Preferred QualificationsExperience with major cloud providers: Azure, AWS, or GCP.Experience working in consulting, nearshore delivery, or multi-country client environments.Knowledge of data governance, cataloging, and data-quality frameworks.Familiarity with agile methodologies and distributed teams.
Apply Now
You will own the entire analytics engineering lifecycle from requirements gathering and data modeling to building ETL/ELT pipelines and delivering high-quality reporting and analytics solutions.
Key Responsibilities:
Data Architecture & ModelingLead end-to-end data-warehouse implementations, including requirements discovery, solution design, development, and deployment.Build and maintain scalable data models (conceptual, logical, and physical) following industry best practices (e.g., Kimball, Data Vault).Translate business needs into clear technical specifications, documentation, and data requirements.Establish and enforce data architecture standards, schemas, and naming conventions.
ETL/ELT Pipeline DevelopmentDesign, develop, and optimize automated ETL/ELT workflows using tools such as Pentaho, TimeXtender, DBT, Azure Data Factory, or similar.Create transformation logic, data-quality validation, and workflow orchestration for complex integrations.Implement robust monitoring, quality checks, and performance optimization across all pipelines.Ensure data accuracy, consistency, and reliability across source and target systems.
Analytics & Reporting EnablementDeliver analytics-ready datasets for BI platforms such as Power BI, Tableau, Looker, or Qlik.Collaborate closely with data analysts, BI developers, and business teams to enable advanced reporting and insights.Optimize data structures for performance, usability, and scalability within reporting environments.
Client Collaboration & LeadershipAct as a technical lead for international client engagements across multiple time zones.Lead requirements workshops, solution walkthroughs, and technical presentations with senior stakeholders.Collaborate with global engineering, analytics, and consulting teams.Mentor junior engineers and contribute to best-practice development across the organization.
Required Qualifications5+ years of experience as an Analytics Engineer, Data Engineer, or Data Warehouse Engineer.Proven experience owning end-to-end data-warehouse implementations.Strong hands-on experience with ETL/ELT tools: Pentaho, TimeXtender, DBT, Azure Data Factory, or similar platforms.Advanced proficiency in SQL and experience with modern cloud data warehouses (SQL Server, Snowflake, BigQuery, Redshift, Azure Synapse, MySQL, PostgreSQL).Expert understanding of data modeling principles and dimensional modeling frameworks.Experience documenting business requirements, technical specifications, data mappings, and process flows.Familiarity with Git-based version control and CI/CD for data pipelines.English proficiency at C1 level (Business Proficient) - capable of leading client meetings, presenting solutions, and writing technical documentation in English.
Preferred QualificationsExperience with major cloud providers: Azure, AWS, or GCP.Experience working in consulting, nearshore delivery, or multi-country client environments.Knowledge of data governance, cataloging, and data-quality frameworks.Familiarity with agile methodologies and distributed teams.
Apply Now