Staff Data Engineer
New
Fully remote-friendly work environment within Brazil.Full-TimeStaff
Salary not disclosed
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Job Details
- Languages
- Advanced English communication skills, both written and spoken.
- Experience
- 7+ years
- Required Skills
- PythonSQLKafkaCI/CDScalaData modelingDistributed Systems
Requirements
- 7+ years of professional experience in data engineering, including ownership of complex enterprise data platform initiatives.
- Strong background in distributed systems architecture and large-scale data platform design.
- Expert-level proficiency in Python, Scala, and SQL.
- Extensive experience with cloud-native data platforms, enterprise data warehouses, and modern data ecosystems.
- Advanced knowledge of data orchestration, transformation frameworks, and large-scale data processing technologies.
- Hands-on experience with real-time streaming technologies such as Kafka, Kinesis, Pub/Sub, or similar platforms.
- Strong expertise in data modeling, data integration, and data transformation methodologies.
- Deep understanding of data governance, quality assurance, compliance requirements, and security best practices.
- Experience implementing containerized environments, CI/CD pipelines, and automation processes for data platforms.
- Proven experience building and maintaining data pipelines for production AI and machine learning systems.
- Demonstrated leadership experience mentoring engineers and influencing technical direction across teams.
- Strong communication skills with the ability to explain complex technical concepts.
- Practical expertise using modern AI-assisted development tools.
- Excellent analytical thinking and problem-solving capabilities.
- Advanced English communication skills, both written and spoken.
Responsibilities
- Define and lead data architecture strategies across data lakes, warehouses, pipelines, and enterprise data platforms.
- Design, build, and optimize scalable batch and real-time data processing systems that support business-critical applications.
- Establish and enforce data governance, quality standards, security controls, and compliance frameworks across the data ecosystem.
- Drive modernization initiatives focused on platform performance, scalability, operational efficiency, and cost optimization.
- Develop monitoring, logging, alerting, and automation capabilities to improve reliability and observability of data systems.
- Design and implement data contracts, event-driven architectures, and integrations with APIs, middleware, and third-party platforms.
- Lead the development of data infrastructure supporting AI and machine learning workloads, including feature stores, embeddings, vector databases, RAG pipelines, and training/inference workflows.
- Collaborate closely with technical and business stakeholders to align data strategy with organizational objectives.
- Establish engineering standards, best practices, and architectural guidelines that elevate data engineering quality across teams.
- Mentor and support junior and mid-level engineers while fostering a culture of technical excellence and continuous learning.
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