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Open nowPosted 5 hours ago

Senior Data Engineer (Databricks & AI Platforms) (4809)

Gupy (Portal de Vagas)80,876 open roles

Where
São Bernardo do Campo, São Paulo, Brazil
Work mode
Hybrid
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Your applicationOpen nowSenior Data Engineer (Databricks & AI Platforms) (4809)Gupy (Portal de Vagas) · São Bernardo do Campo, São Paulo, Brazil

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The clock on this job

Early applications get read.

8.2% of postings close within 7 days. Measured by our own scanner across the market. Gupy (Portal de Vagas) postings stay open a median of 3 days.

Share of postings closed within
  1. 1.9%1 day
  2. 3.8%3 days
  3. 8.2%7 days
  4. 15.2%14 days
  5. 34.1%30 days
This job: posted 5 hours ago

Gupy (Portal de Vagas) median: 3 days open

The posting

Come work for a large global financial and insurance products company! This is your chance !!Start a successful career in a renowned company in the international market! Great opportunity!Global insurance and asset management company seeks a responsible, organized, dynamic and team-oriented person.Responsabilidades e atribuiçõesThe Senior Data Engineer is responsible for designing, building, and optimizing scalable data platforms and pipelines that support analytics, business intelligence, machine learning (ML), and AI-driven solutions. This role partners with data scientists, AI engineers, architects, and business stakeholders to deliver trusted, high-quality data products using Databricks, cloud technologies, and modern data engineering practices. The position also serves as a technical leader in enabling enterprise AI and Generative AI initiatives through robust, secure, and governed data platforms.Key Responsibilities:Design, develop, and maintain scalable data pipelines and data products using Databricks, Spark, Python, and SQL;Build and optimize batch, streaming, and real-time data integration solutions from enterprise and third-party data sources;Implement Databricks Lakehouse architectures utilizing Delta Lake and Medallion design patterns;Develop and maintain data products that support analytics, predictive modeling, machine learning, and Generative AI applications;Collaborate with Data Scientists and AI Engineers to prepare, transform, and govern data for AI and ML use cases;Design and implement feature engineering pipelines and support ML lifecycle processes;Develop data solutions that support Retrieval Augmented Generation (RAG), vector search, semantic search, and LLM-based applications;Optimize Spark jobs, SQL workloads, and data processing frameworks for performance, scalability, and cost efficiency;Implement data quality, observability, lineage, governance, and monitoring capabilities;Ensure compliance with data privacy, security, and responsible AI standards;Contribute to CI/CD, Infrastructure-as-Code, and DataOps practices across the data platform;Mentor junior engineers and promote engineering best practices across the organization.Requisitos e qualificaçõesRequired Qualifications:Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field;7+ years of experience in data engineering, ETL development, or large-scale data platform engineering;3+ years of hands-on experience with Databricks and Apache Spark;Strong proficiency in Python, SQL, and distributed data processing frameworks;Experience building cloud-based data lakes, data warehouses, and Lakehouse architectures;Experience supporting AI, machine learning, or advanced analytics initiatives;Strong understanding of data modeling, data governance, and enterprise data management practices;Experience developing and optimizing large-scale data pipelines in AWS, Azure, or Google Cloud.Preferred Qualifications:Experience with Databricks Delta Lake, Unity Catalog, Delta Live Tables, MLflow, Mosaic AI, and Databricks Workflows;Hands-on experience supporting Generative AI, Large Language Models (LLMs), RAG architectures, vector databases, or AI-powered applications;Familiarity with AI frameworks such as LangChain, Semantic Kernel, OpenAI APIs, Hugging Face, or similar technologies;Experience with feature stores, model training pipelines, and machine learning operationalization (MLOps);Experience with Kafka, Event Hub, or other streaming technologies;Databricks Certified Data Engineer Professional or equivalent cloud certification.Key Competencies:Databricks Platform Engineering;Apache Spark Development;AI & Machine Learning Data Engineering;Generative AI Data Solutions;Lakehouse Architecture;Data Modeling & Data Warehousing;Data Governance & Security;Data Observability & Reliability Engineering;Cloud Data Platforms (AWS/Azure);DataOps, CI/CD & Automation;Technical Leadership & Mentoring.Success Measures:Delivery of scalable, reliable, and secure data platforms supporting analytics, AI, and business operations;Successful enablement of AI and Generative AI use cases through high-quality, governed data products;Improved data quality, pipeline reliability, and platform performance;Increased automation, operational efficiency, and reuse of engineering frameworks;Adoption of data engineering standards and best practices across development teams;Measurable improvements in AI/ML solution delivery speed and business value realization.Informações adicionaisModelo de contratação:PJ.Forma de atuação:Híbrido (3x por semana presencial no escritório de Pinheiros/SP).

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