Data Migration Consultant responsible for migrating various data types into Microsoft Dynamics 365 CE. Analyze structures, develop mapping documentation, and ensure data integrity during migration.
About the role
- Sr GenAI Data Engineer at an insurance company developing AI solutions and data strategies. Leading innovative projects while mentoring teams and implementing best practices in data engineering.
Responsibilities
- Develop AI-driven systems to improve data capabilities, ensuring compliance with industry best practices.
- Implement efficient Retrieval-Augmented Generation (RAG) architectures and integrate with enterprise data infrastructure.
- Collaborate with cross-functional teams to integrate solutions into operational processes and systems supporting various functions.
- Stay up to date with industry advancements in AI and apply modern technologies and methodologies to our systems.
- Design, build and maintain scalable and robust real-time data streaming pipelines using technologies such as GCP, Vertex AI, S3, AWS Bedrock, Spark streaming, or similar.
- Develop data domains and data products for various consumption archetypes including Reporting, Data Science, AI/ML, Analytics etc.
- Ensure the reliability, availability, and scalability of data pipelines and systems through effective monitoring, alerting, and incident management.
- Implement best practices in reliability engineering, including redundancy, fault tolerance, and disaster recovery strategies.
- Collaborate closely with DevOps and infrastructure teams to ensure seamless deployment, operation, and maintenance of data systems.
- Mentor junior team members and engage in communities of practice to deliver high-quality data and AI solutions while promoting best practices, standards, and adoption of reusable patterns.
- Apply AI solutions to insurance-specific data use cases and challenges.
- Partner with architects and stakeholders to influence and implement the vision of the AI and data pipelines while safeguarding the integrity and scalability of the environment.
Requirements
- 8+ years’ Strong hands-on experience programming skills in Python.
- 7+ years of data engineering Strong hands-on experience including Data solutions, SQL and NoSQL, Snowflake, ETL/ELT tools, CICD, Bigdata, Cloud Technologies (AWS/Google/AZURE), Python/Spark.
- 3+ years of data engineering experience focused on supporting Generative AI technologies.
- 2+ years Strong hands-on experience implementing production ready enterprise grade GenAI data solutions.
- 3+ years’ experience in implementing Retrieval-Augmented Generation (RAG) pipelines, integrating retrieval mechanisms with language models.
- 3+ years’ Experience of vector databases and graph databases, including implementation and optimization.
- 3+ years’ Experience in processing and leveraging unstructured data for GenAI applications.
- 3+ years’ Proficiency in implementing scalable AI driven data systems supporting agentic solution (AWS Lambda, S3, EC2, Langchain, Langgraph).
- 3+ years’ Experience with building AI pipelines that bring together structured, semi-structured and unstructured data. This includes pre-processing with extraction, chunking, embedding and grounding strategies, semantic modeling, and getting the data ready for Models and Agentic solutions.
Benefits
- Short-term or annual bonuses
- Long-term incentives
- On-the-spot recognition
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