Responsabilidades e atribuições
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
- We are seeking a highly skilled Senior Data Engineer to design, build, and optimize modern data platforms that enable advanced analytics, AI/ML, and business intelligence solutions
- The ideal candidate will possess deep expertise in Databricks, cloud-based data engineering, data architecture, and modern software engineering practices
- This role will provide technical leadership, establish engineering standards, and drive the development of scalable, secure, and reliable data solutions supporting enterprise-wide initiatives
- Key ResponsibilitiesData Platform Engineering:Design, develop, and maintain scalable data pipelines using Databricks, Spark, and cloud-native technologies
- Build and optimize batch and real-time data ingestion frameworks
- Develop reusable engineering patterns, frameworks, and accelerators for enterprise data solutions
- Implement data quality, observability, lineage, and governance capabilities across the data ecosystem
- Support large-scale data modernization and cloud migration initiatives
- Databricks Engineering:Design and implement Delta Lake architectures and Medallion data models
- Build optimized ETL/ELT pipelines using Databricks notebooks, workflows, and Delta Live Tables
- Establish performance tuning, cost optimization, and workload management best practices
- Leverage Unity Catalog for data governance, security, and metadata management
- Implement CI/CD pipelines and Infrastructure-as-Code for Databricks deployments
- Cloud Data Engineering:Design cloud-native data architectures across Azure and AWS environments
- Integrate enterprise data sources including SQL Server, Oracle, APIs, SaaS platforms, and streaming platforms
- Build resilient and secure data services supporting high availability and disaster recovery requirements
- Partner with infrastructure and security teams to implement cloud security controls and compliance standards
- AI and Advanced Analytics Enablement:Build and optimize data products supporting AI, machine learning, and generative AI workloads
- Develop feature engineering pipelines and curated datasets for model training and inference
- Support vector databases, semantic search, RAG (Retrieval-Augmented Generation), and LLM-powered applications
- Collaborate with Data Scientists and AI Engineers to operationalize machine learning solutions
- Implement MLOps and DataOps practices to support scalable AI delivery
- Technical Leadership:Serve as a technical lead for complex data engineering initiatives
- Define architecture standards, engineering best practices, and development guidelines
- Mentor junior and mid-level engineers
- Conduct architecture reviews and provide technical recommendations
- Drive adoption of automation, observability, and platform engineering principles
