Chief Data Architect
4 semanas atrás
About Us We are seeking a highly skilled Data Engineer to join our team. The ideal candidate will be responsible for designing, building, and maintaining scalable data pipelines and ingestion processes that support analytics and AI use cases. The successful candidate will have strong expertise in SQL, including advanced joins, CTEs, window functions, and performance tuning. They will also have hands-on experience building ETL/ELT pipelines using modern orchestration tools and proficiency in Python for data processing and pipeline development. Key Responsibilities Design and implement 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 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 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 Perks and Benefits Celebrations Special discounts Entertainment area Modern Work Spaces Great work environment Private medical insurance
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Brasil beBeeDataEngineer Tempo inteiroJob Overview Familiarity with major cloud providers is crucial for developing and implementing scalable data pipelines. To succeed, proficiency in ingestion tools (Kafka, AWS Glue) and formats (Iceberg, Parquet) ensures seamless data ingestion and storage. A strong foundation in SQL-based frameworks and orchestration tools (dbt, Glue, Airflow) enables...
