[Job - 22687] Master Data Developer, Brazil

We are looking for a Data Platform Developer to join our team in our development center, working with a major US client in a fast-paced, high-impact environment. In this role, you will architect and implement robust data pipelines and modern analytics platforms, working in close collaboration with cross-functional teams across the US and Brazil. You will be responsible for building scalable data solutions leveraging modern cloud-native tools.

Fluent English communication is essential for engaging with our global stakeholders and ensuring alignment across distributed teams.

- Solid experience as a Data Developer

- Strong SQL expertise with the ability to optimize, refactor, and validate large-scale data transformations.

- Proficiency in Python (or similar language) for scripting and automation of data workflows.

- Hands-on experience with Snowflake, including performance tuning, data governance, masking, and workload management.

- Advanced knowledge and production experience with dbt for transformation logic, testing, documentation, and CI/CD integrations.

- Proven experience implementing Data Vault 2.0 models, including Hubs, Links, Satellites, PIT tables, and business vault patterns using AutomateDV or similar frameworks.

- Experience orchestrating ETL/ELT pipelines using Airflow, with knowledge of DAG structuring, dependency management, and dynamic task generation.

- Familiarity with modern data orchestration tools, such as Prefect, Dagster, or AWS Glue.

- Comfortable working in environments using CI/CD pipelines with GitHub Actions, integrating dbt, testing, and deployment to Snowflake or similar platforms.

- Solid understanding of data modeling best practices, including normalization, dimensional modeling, and historization.

- Ability to translate business requirements into scalable data architectures, and to communicate technical concepts effectively with stakeholders.

- Experience with data observability tools like Monte Carlo, Datafold, or Great - - Expectations to ensure trust in data pipelines.

- Experience with containerization technologies like Docker or Kubernetes for reproducible environments and scalable deployments.

- Exposure of SAP

- Knowledge of GraphQL, RESTful APIs, or streaming ingestion frameworks such as Kinesis or Firehose.

- Experience working in hybrid architectures, including data lakehouses, or multi-cloud strategies.

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