Engenheiro de Dados PL/SR - Databricks
New
J
JobgetherData Engineering
BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- PythonSQLGCPMachine LearningSparkBigQueryDatabricksRscikit-learnMLOps
Requirements
- Advanced proficiency in Python or R for data manipulation, analytics, and production-ready ML implementation.
- Strong experience with advanced SQL for extraction, transformation, and large-scale data cleansing.
- Proven experience with Machine Learning and predictive modeling using tools like Scikit-Learn, XGBoost, or LightGBM.
- Solid understanding of the end-to-end ML lifecycle, including versioning, monitoring, and automated pipelines.
- Professional experience with Google Cloud Platform, Databricks, Apache Spark, and BigQuery.
- Strong knowledge of statistics, statistical inference, and experimental design (A/B testing).
- Experience designing scalable data architectures and applying governance, quality, and security practices.
- Ability to connect analytical outcomes to business objectives and measurable value.
- Experience defining and monitoring business and model performance metrics.
- Strong problem-solving skills to develop innovative solutions for complex analytical challenges.
- Experience in the Healthcare sector is considered a plus.
- Strong communication, collaboration, and technical ownership.
Responsibilities
- Translate business challenges into scalable data, Analytics, AI, and Machine Learning solutions.
- Design, develop, and operationalize end-to-end data and ML solutions including data preparation and production monitoring.
- Build and maintain scalable data processing solutions using Databricks, Apache Spark, BigQuery, and Google Cloud Platform.
- Implement MLOps practices for automation, pipeline management, and model monitoring.
- Design and evolve cloud-based data architectures with a focus on security, governance, and quality.
- Establish engineering best practices including documentation, monitoring, and quality controls.
- Act as a technical reference for Data and AI initiatives to support architectural decisions.
- Evaluate emerging technologies in Data Engineering and Generative AI.
- Develop and monitor business performance indicators to translate analytical results into actionable insights.
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