Sr Data Engineering Specialist, Sumaré
On-siteSão Paulo, São Paulo, Brazil
EXPIREDSão Paulo, São Paulo, BrazilOn-siteFull TimeSenior LevelLarge
Full TimeSenior LevelLarge
Job Summary
Design, build, and maintain scalable data pipelines for structured and unstructured data within a modern cloud-based Lakehouse platform using Databricks, Delta Lake, and AWS. Develop batch and streaming pipelines, optimize for performance and cost efficiency, and enable AI and GenAI use cases through feature engineering and document ingestion. Build logical and physical data models, implement data quality checks, and collaborate with cross-functional teams to deliver production-grade data solutions aligned with governance standards. Work at least four days a week on-site in Sumaré/SP.
Required Qualifications
- Bachelor's degree or higher in Computer Science, Engineering, or related field
- Senior experience in data engineering, data platforms, or related roles
- Strong proficiency in SQL and Python
- Hands-on experience building scalable data pipelines and data processing workflows
- Experience working with distributed processing systems such as Apache Spark
- Experience with modern cloud data platforms - Databricks or similar
- Experience working with cloud platforms such as AWS (S3, Glue, etc.)
- Understanding of data modeling, data transformation, and data warehousing concepts
- Experience working in cross-functional engineering environments
- Proficiency in English
- Work location: This role follows an on-site working model, requiring the employee to work at least four days a week in Sumaré/SP
Desired Qualifications
- Experience with Delta Lake, Unity Catalog, and Lakehouse architectures
- Familiarity with metadata and catalog systems such as DataHub
- Experience with workflow orchestration tools (Temporal, Airflow, Step Functions)
- Experience with PySpark
- Experience supporting AI/ML use cases, including feature engineering and dataset preparation
- Familiarity with LLM-based applications, vector databases, or GenAI pipelines
- Experience with streaming technologies (Kafka, Kinesis, Spark Streaming)
- Exposure to CI/CD pipelines and infrastructure-as-code concepts
- Experience with APIs and event-driven architectures
- Understanding of data governance principles including lineage, cataloging, and access control
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