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

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 scala