Salary
≈ $91k – $205k per year (Estimated)
Location
Remote (Argentina, Mexico, Costa Rica)
Seniority
Senior · 5+ years exp
Confirmed on the employer's own hiring board on Oct 1, 2026. First seen by Alion on Jul 17, 2026.
Overview
Company
Impact
Profile match
Svitla Systems is a global digital solutions and custom software engineering company headquartered in California, with delivery centers across North America, Latin America, Europe, and Asia. Founded in 2003, the company offers end-to-end IT services, including cloud architecture, AI/machine learning integration, data engineering, DevOps, and mobile and web application development.
Svitla Systems Inc. is seeking a Data Architect/Engineer for a full-time (40 hours per week) position in LATAM. Our client is a leading global toy manufacturer with an award-winning, robust portfolio of wholly owned and licensed brands. Founded in 1997, the company celebrates imaginative play with a progressive focus on identifying emerging trends and turning them into high-quality products for consumers of all ages. It engages consumers through innovative play experiences with popular brands. In addition to toys, offerings include Metaverse gaming, costumes, and pet products.
Requirements:
- Industry Experience: Previous experience working within the Consumer Packaged Goods (CPG) industry is highly preferred.
- Technical Expertise: 5+ years of deep expertise in Python and SQL.
- Certified Databricks data engineer plus vast experience in dbt Cloud, and Terraform.
- Strong cloud proficiency within AWS environments.
- Methodologies: Deep understanding of the Medallion Architecture, advanced data modeling, and modern ELT/ETL patterns.
- AI/ML Familiarity: Proven experience managing data pipelines and scripts geared toward machine learning lifecycles and MLOps.
Responsibilities:
- Architecture & Engineering: Design, build, and maintain scalable data pipelines utilizing the Medallion Architecture (Bronze, Silver, Gold) within Databricks.
- Infrastructure as Code & DataOps: Oversee the data infrastructure deployment using Terraform and establish rigorous CI/CD and DataOps best practices.
- Data Ingestion & ELT/ETL: Standardize and optimize ingestion frameworks utilizing tools like LakeFlow and Workato alongside complex dbt transformations.
- Data Modeling: Act as the subject matter expert on advanced data modeling techniques to ensure high performance, data integrity, and cost efficiency in Databricks.
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