What are the responsibilities and job description for the Data Engineer (Analytics/Modeling) position at Jobgether?
This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Data Engineer (Analytics/Modeling) in Brazil.
This role is centered on building and evolving a modern, high-performance data platform that powers analytics across a global marketplace ecosystem. You will work on transforming legacy data workflows into scalable, production-grade data models that enable reliable, real-time insights for business-critical decision-making. Acting as a key contributor within a specialized analytics engineering team, you will design and optimize data pipelines, ensuring strong data quality, observability, and performance. The environment is highly technical and collaborative, involving modern cloud data tools and engineering best practices. Your work will directly support multiple business units by delivering trusted datasets that drive product, operational, and hiring insights. This is a high-impact role ideal for engineers passionate about data modeling, analytics engineering, and modern data stack architectures.
\n- Design, build, and maintain scalable data models and pipelines supporting analytics and marketplace intelligence use cases.
- Transform legacy ETL workflows into modern ELT processes using tools such as dbt and cloud-native architectures.
- Develop and optimize complex SQL queries for data transformation, validation, and analytical reporting.
- Build Python-based data workflows, automation scripts, and pipeline components to support scalable data processing.
- Design and maintain performant data structures within Snowflake, ensuring efficiency and reliability.
- Implement and enforce data quality frameworks, validation rules, and pipeline health monitoring practices.
- Collaborate with cross-functional teams to ensure analytics datasets are accurate, accessible, and production-ready.
- Support integration of data models with BI tools and downstream analytics systems.
Requirements:
- 3–5 years of experience in data engineering, analytics engineering, or advanced data-focused roles.
- Strong expertise in SQL for complex transformations, debugging, and performance optimization.
- Hands-on experience with Python for data processing, automation, and pipeline development.
- Proven experience working with Snowflake or similar cloud data warehousing platforms.
- Practical experience building ELT pipelines using dbt in production environments.
- Familiarity with AWS cloud services such as S3, EC2, or related data infrastructure tools.
- Strong understanding of data quality, validation, and reliability engineering principles.
- Experience working with modern orchestration tools such as Dagster or Airflow is a plus.
- Exposure to BI tools such as Tableau, Looker, or Power BI is an advantage.
- Strong analytical thinking and ability to translate business needs into data solutions.
Benefits:
- Fully remote work from anywhere in LATAM.
- Contract-based full-time engagement with international teams.
- Exposure to modern data stack technologies (Snowflake, dbt, Dagster).
- Opportunity to work on large-scale marketplace analytics systems.
- Collaboration with experienced engineers and global technology experts.
- Strong focus on technical excellence and continuous learning.
- High-impact role influencing data-driven decision-making across business units.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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