Senior Architect, Data Analytics /AI-ML

Responsibilities

Job Description

Design and develop a scalable Cloud-native data analytics platform and solutions
Own architecture and provide technical leadership to multiple teams and mentor junior engineers on standards and best practices
Hands-on coding > 30% of the time
Assess, benchmark and select data analytics technologies
Own and enforce well-architecture principles such as operational efficiency, scalability, availability, performance, cost and data security
Identify areas of architectural risk and work with other engineering teams to address them
Collaborate with stakeholders including product managers, data scientists and insurance domain experts to define requirements and design solutions. To be successful you must drive consensus and balance the needs of many different constituencies
Represent our technical strategy and architecture with prospective customers during sales visits (typically CIOs and Heads of IT)

Qualifications

BS or MS degree (Computer Science, Engineering, Mathematics, Statistics or related field)
5+ years of required work experience with proven track record architecting and delivering scalable data analytics products and solutions
Extensive experience working on a public cloud-like AWS and its associated tech stack (e.g. EC2, Kubernetes(EKS), ECS, EMR, S3, SageMaker, Redshift, Athena, Airflow, etc.)
Ability to design large scale distributed Big Data processing systems using technologies such as Hadoop, Spark, Kafka, etc. and open data formats such as Apache Hudi, Iceberg, Parquet, etc..
Excellent software design and development skills using languages such as Python, Java, Scala, etc.
Experience with microservices architecture patterns and container technologies such as Docker and Kubernetes
Hands-on knowledge of cyber-security concepts in operating systems, cross-platform systems, software, network protocols and Cloud infrastructure
Solid understanding of CI/CD and DevOps and experience with meeting operational SLAs
Collaborative leadership style and ability to earn the respect of a talented engineering team
Excellent verbal and written communications skills

Preferred

Experience in InsurTech, FinTech, and/or P&C domain knowledge
Experience with data science and machine learning techniques, and operationalizing analytic models (MLOps)
Experience or sound understanding of GenAI LLM models, frameworks, and tools