Senior Data Engineer (AI Data Platform)

Applaudo Studios; Brasil; Presencial; BRL 180 000 - 300 000; Tempo integral

Resumo da oferta

Applaudo Studios is seeking a Senior Data Engineer to design scalable data platforms powering AI-driven analytics. The role focuses on data architectures, ETL/pipeline optimization, and cloud-native solutions to deliver reliable data for engineering and AI teams.

This 6-month temporary opportunity involves hands-on work with Snowflake, dbt, Dagster, and AWS S3, emphasizing Medallion Architecture and strong collaboration across cross-functional teams. Fluent English is required.

Qualificações

• Bachelor’s degree or equivalent professional experience.
• 5+ years as a Data Engineer or similar role.
• Design scalable data architectures and data models.
• Hands-on with Medallion Architecture (Bronze-Silver-Gold).
• Experience building ETL and data ingestion pipelines.
• Advanced SQL proficiency.
• Production with PostgreSQL or Supabase.
• Hands-on with Snowflake.
• dbt for data transformation.
• Experience with AWS S3.
• Dagster or similar workflow tools.
• Familiarity with graph databases.
• AI/ML concepts including embeddings and AI workflows.
• Git and collaborative software development.
• Strong analytical, problem-solving, and communication skills.
• English proficiency (B2+/C1).

Responsabilidades

• Design, build, and maintain scalable data architectures and data models.
• Develop and optimize ETL and data ingestion pipelines following Medallion Architecture principles.
• Build and maintain Snowflake data warehouse solutions and dbt transformation models.
• Develop workflow orchestration pipelines using Dagster or similar technologies.
• Manage and optimize cloud-based data storage using AWS S3.
• Design and maintain graph-based data models where appropriate.
• Support Entity Matching pipelines and related data structures.
• Collaborate closely with AI and Data Science teams to enable reliable data consumption for AI applications.
• Provide technical guidance and promote data engineering best practices across the team.
• Participate in Agile ceremonies and contribute to continuous improvement initiatives.

Conhecimentos

ETL pipelines

Snowflake

dbt

Dagster

AWS S3

SQL

PostgreSQL

Medallion Architecture

Data modeling

AI concepts

Git

English (B2+/C1)

Formação académica

Bachelor’s Degree in Computer Science/Software Engineering/Information Systems or equivalent

Ferramentas

dbt

Snowflake

Dagster

PostgreSQL

Supabase

AWS S3

Graph databases

Descrição da oferta de emprego

About You

You are a Senior Data Engineer passionate about building scalable data platforms that power AI-driven products and advanced analytics. You thrive in collaborative environments where you can design modern data architectures, optimize data pipelines, and enable engineering and AI teams with reliable, high-quality data solutions.

You enjoy solving complex data challenges, implementing cloud-native architectures, and continuously improving data engineering practices. You are proactive, analytical, and committed to building robust, scalable, and maintainable data platforms.

Note: This is a 6-month temporary opportunity with the possibility of extension.

You Bring to Applaudo the Following Competencies:

• Bachelor’s Degree in Computer Science, Software Engineering, Information Systems, or a related field is desired, or equivalent professional experience.
• 5+ years of experience as a Data Engineer or in a similar role.
• Strong experience designing scalable data architectures and data models.
• Hands-on experience implementing Medallion Architecture (Bronze, Silver, Gold).
• Experience building ETL and data ingestion pipelines.
• Advanced SQL proficiency.
• Production experience with PostgreSQL or Supabase.
• Hands-on experience with Snowflake.
• Experience using dbt for data transformation.
• Experience working with AWS, particularly S3.
• Experience using Dagster or similar workflow orchestration tools.
• Familiarity with graph databases.
• Understanding of AI/ML concepts, including embeddings and AI-driven data workflows.
• Experience using Git and collaborative software development practices.
• Strong analytical, problem-solving, and communication skills.
• Upper-Intermediate to Advanced English proficiency (B2+/C1).

You Will Be Accountable for the Following Responsibilities:

• Design, build, and maintain scalable data architectures and data models.
• Develop and optimize ETL and data ingestion pipelines following Medallion Architecture principles.
• Build and maintain Snowflake data warehouse solutions and dbt transformation models.
• Develop workflow orchestration pipelines using Dagster or similar technologies.
• Manage and optimize cloud-based data storage using AWS S3.
• Design and maintain graph-based data models where appropriate.
• Support Entity Matching pipelines and related data structures.
• Collaborate closely with AI and Data Science teams to enable reliable data consumption for AI applications.
• Provide technical guidance and promote data engineering best practices across the team.
• Participate in Agile ceremonies and contribute to continuous improvement initiatives.

About Us

We Are Engineered Different.

At Applaudo, talented people design, build, and scale meaningful, AI-powered solutions that create real business impact. As an AI-native organization, we collaborate across design, development, cloud, data, and artificial intelligence to turn ideas into scalable products that transform how companies operate, make decisions, and grow.

We are building a high-performance culture grounded in five values:Empowering Excellence, Collaborative Teamwork, Unsolicited Respect, Consistent Transparency, and Efficient Communication. These define how we work, how we support one another, and how we hold ourselves accountable.

Applaudois a place for people who want to learn fast, take ownership, and work alongside strong teams they are proud to belong to. Joining us means being part of an organization that is evolving intentionally, investing in modern ways of working, and leading AI-native transformation at scale.