Data Engineer Opportunity

Há 4 dias


Rio de Janeiro RJ, Brasil beBeeData Tempo inteiro

Senior Data Engineer Position As a Senior Data Engineer, you will play a key role in designing and building scalable data pipelines and ingestion processes that support analytics and AI use cases. You will collaborate with analytics, AI/Data Science, and product teams to understand data requirements and SLAs. Key Responsibilities: Design, build, and maintain scalable data pipelines and ingestion processes supporting analytics and AI use cases. Implement and optimize ETL/ELT workflows with attention to performance, reliability, and cost. Design and evolve data models and curated layers to support reporting, analytics, and downstream systems. Collaborate with analytics, AI/Data Science, and product teams to understand data requirements and SLAs. Support AI and advanced analytics features by providing clean, well-structured, and reliable datasets. Apply best practices around data quality, validation, monitoring, and observability. Write maintainable, well-documented data code and contribute to shared standards and patterns. Participate in architecture discussions and help improve overall data platform design. Requirements: Bachelor's degree or higher in Computer Science, Computer Engineering, or related field — or equivalent professional experience. 5+ years of experience as a Data Engineer, building and operating production-grade data pipelines. Strong expertise in SQL, including advanced joins, CTEs, window functions, and performance tuning. Experience designing data models and analytical structures (dimensional models, facts, dimensions, SCDs). Hands-on experience building ETL/ELT pipelines using modern orchestration tools (Airflow, Dagster, DBT, or similar). Proficiency in Python for data processing and pipeline development (PySpark is a strong plus). Solid experience working with cloud platforms (AWS, Azure, or GCP) for data storage and processing. Familiarity with data platforms such as Snowflake, Databricks, PostgreSQL, or similar. Experience using Git and CI/CD practices as part of a modern data engineering workflow. Exposure to supporting AI/Data Science initiatives, such as data enablement for models, embeddings, entity matching, or advanced analytics (nice to have). Familiarity with graph databases, embeddings, or AI integrations from a data engineering perspective (nice to have). Ability to work independently and collaborate effectively with analysts, ML engineers, and product teams. Advanced English proficiency (B2+), able to work with global stakeholders. Benefits: Celebrations Special discounts* Entertainment area* Modern Work Spaces* Great work environment Private medical insurance* *Benefits may vary according to your location and/or availability.



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