Blanc Labs
Data Engineer
Vaga remota de Data Engineering com fit claro de localização do candidato.
Publicada24 de jul. de 2026
Países elegíveis24 países aceitos
Sinal de senioridadeMiddle
Modelo de trabalhoRemoto
Locais aceitos para candidatos
Resumo da vaga
Data Engineer
Requisitos e responsabilidades
Conteúdo da vaga extraído em seções para revisão mais rápida.
What You'll be Doing:
- Design, build, and maintain scalable data pipelines using Databricks and Apache Spark
- Develop and optimize ETL/ELT processes to ingest, transform, and load data from diverse source systems
- Implement Change Data Capture (CDC) solutions to enable real-time and near-real-time data synchronization
- Write clean, efficient, and maintainable code in Python for data processing and automation
- Collaborate with data architects and analysts to translate business requirements into robust data pipeline designs
- Monitor, troubleshoot, and optimize data pipeline performance, reliability, and cost efficiency
- Ensure data quality, consistency, and integrity across ingestion, transformation, and storage layers
- Support integration of structured and unstructured data sources into unified data platforms
- Participate in code reviews and promote data engineering best practices across the team
- Document data pipelines, transformations, and architecture for team visibility and maintainability
- Collaborate with cross-functional teams to support analytics, reporting, and downstream AI/ML use cases
What You'll Need to Be Successful:
- 3+ years of experience in data engineering or a related field
- Strong hands-on experience with Databricks for data processing and analytics workloads
- Proficiency with Apache Spark for large-scale distributed data processing
- Experience implementing CDC solutions and tools (e.g., Debezium or similar)
- Strong programming skills in Python for data engineering tasks
- Solid understanding of SQL and relational database concepts
- Experience building and maintaining ETL/ELT pipelines in production environments
- Understanding of data modeling principles and data warehousing concepts
- Strong analytical and problem-solving skills
- Good communication skills, with the ability to work across technical and business teams
Preferred Qualifications:
- Experience with cloud platforms (AWS, Azure) and their data services
- Familiarity with orchestration tools (e.g., Airflow, Databricks Workflows)
- Knowledge of data governance and cataloging practices
- Experience with streaming data technologies (e.g., Kafka)
- Experience working in Agile/Scrum environments
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