About this role
- This position is open to candidates located in Colombia or Costa Rica only -
Gorilla Logic is looking for an experienced Senior Data Engineer with strong hands-on expertise in Snowflake, SQL, data modeling, and building scalable data pipelines to support enterprise analytics, business intelligence, and downstream applications. The ideal candidate will have extensive experience designing and implementing data warehouse solutions, particularly building staging, integration, and Golden Layer tables that transform raw data into reliable, analytics-ready datasets.
In this role, you will work closely with engineering and business stakeholders to consolidate data from multiple sources, develop well-structured data models, and ensure that information is accessible and reliable for reporting, business intelligence platforms, and other data-driven applications. We are looking for an autonomous, hands-on engineer who can take ownership of data engineering initiatives, troubleshoot complex data challenges, and contribute to the development of scalable and maintainable data solutions.
Responsibilities
- Design, develop, and maintain scalable data pipelines and data warehouse solutions using Snowflake.
- Build and maintain staging, integration, reporting, and Golden Layer tables to support analytics and downstream applications.
- Consolidate and transform raw data into structured, reliable, and business-ready datasets.
- Implement layered data architectures, including Bronze, Silver, and Gold layers, following modern data engineering practices.
- Design and optimize data models using star schemas, fact tables, dimension tables, and other analytical modeling techniques.
- Develop and optimize complex SQL queries, transformations, and data processing workflows.
- Build and maintain ETL/ELT pipelines to integrate data from multiple enterprise systems and external sources.
- Prepare and structure datasets for consumption by business intelligence tools such as Power BI, Tableau, Looker, or similar platforms.
- Support data integrations with downstream applications, APIs, and business systems.
- Implement data quality checks, validation processes, monitoring, and automated workflows to ensure data accuracy and reliability.
- Identify and resolve data pipeline failures, performance bottlenecks, and data consistency issues.
- Collaborate with business stakeholders to understand reporting, analytics, and data integration requirements.
- Contribute to data architecture discussions, technical decisions, and continuous improvements to data engineering practices.
- Develop well-documented, maintainable, and reusable data solutions that support evolving business needs.
Technical requirements
- 5+ years of professional experience in Data Engineering, including designing and maintaining production data pipelines and data warehouse solutions.
- Strong hands-on experience with Snowflake, including developing, maintaining, and optimizing data warehouse structures.
- Demonstrated experience building staging, integration, reporting, and Golden Layer tables in Snowflake.
- Experience consolidating, transforming, and modeling raw data into analytics-ready datasets for BI platforms and downstream systems.
- Strong knowledge of SQL, including complex queries, transformations, joins, aggregations, and performance optimization.
- Experience designing dimensional data models, including star schemas, fact tables, and dimension tables.
- Hands-on experience building and maintaining ETL/ELT pipelines and data integration workflows.
- Experience preparing and structuring data for consumption by BI and reporting platforms such as Power BI, Tableau, Looker, or similar tools.
- Experience integrating data from multiple sources, including databases, APIs, files, or streaming pipelines.
- Strong understanding of data warehouse architecture, data quality, data consistency, and performance optimization.
- Experience with Python or another programming language used for data processing and automation.
- Experience working with cloud-based data platforms and services, such as AWS or similar enterprise cloud environments.
- Strong troubleshooting, analytical thinking, and problem-solving skills.
- Ability to work independently, take ownership of technical initiatives, and communicate effectively with technical and business stakeholders.
- Strong English communication skills.
Bonus Skills
- Experience with dbt for data transformation and modeling.
- Experience with Apache Airflow, Dagster, or similar workflow orchestration tools.
- Familiarity with Snowflake Dynamic Tables, Streams, Tasks, Materialized Views, and other advanced Snowflake features.
- Experience with Kafka or other real-time data streaming technologies.
- Experience with Snowplow for event tracking, data collection, and ingestion.
- Familiarity with modern data integration tools such as Fivetran or similar solutions.
- Experience designing semantic layers, standardized datasets, or self-service analytics solutions.
- Experience supporting marketing analytics, customer data platforms, or business intelligence initiatives.
- Experience with infrastructure as code, including Terraform.
- Familiarity with AI-assisted development tools and their application in data engineering workflows.