Senior Associate, Cloud Data & Analytics Strategy – Insurance

Role Overview

• Help organisations uncover enterprise insights and drive business results using smarter data analytics
• Assist clients in choosing a platform, defining their data needs and migrating them to a modern cloud data environment using cloud providers such as Azure, Google Cloud Platform, Amazon Web Services, Snowflake, Databricks or Teradata
• Work as part of a team of problem solvers, helping to solve complex business issues from strategy to execution
• Use a broad range of tools and techniques to extract insights from current industry or sector trends
• Review your work and that of others for quality, accuracy and relevance
• Seek and embrace opportunities which give exposure to different situations, environments and perspectives
• Use straightforward communication, in a structured way, when influencing and connecting with others.

Requirements

• Minimum Degree Required: Bachelor Degree
• Minimum Years of Experience: 4 year(s)
• Certification in one of the following cloud platforms
• AWS/Azure/GCP
• Demonstrating an expertise in developing and implementing data or analytics-driven strategies to drive business growth and optimize decision-making
• Defining data management and data/analytics governance strategy and align data initiatives with organizational goals
• Conducting data/analytics strategy refresh on a regular basis and managing overall data strategy program success
• Delivering strategy and transformation projects
• Understanding and experience with modern cloud data architectures and engineering for one or more of the following cloud providers
• AWS, Azure, GCP
• Implementing cloud data architecture and data integration patterns for one or more of the cloud providers (AWS Glue, Azure Data Factory, Event Hub, Databricks, etc.), storage and processing (Redshift, Azure Synapse, BigQuery, Snowflake)
• Infrastructure as code (CloudFormation, Terraform)
• Understanding and thorough knowledge of Data Warehousing concepts (normalization, OLAP, OLTP, Vault data model, graphs, star & snowflake schemas)
• Applying knowledge and work experience in Big data engineering (Hadoop, Spark, Scala, Kafka) and ETL/ELT pipeline development (tools: IICS/AWS Glue/SAP BODS/Matillion/DBT/Abinitio/SSIS/SnapLogic); preferable in P&C/L&A Insurance data warehouse
• Developing file and object-based storage solutions using Azure ADLS 2.0 or AWS S3
• Applying knowledge in SQL, report generation using visualization tools such as Tableau/Power BI/Cognos, programming using Python/Spark
• Designing and developing advanced analytics solutions, AI/ML models, and operationalizing based on ML Ops process
• Understanding of enterprise data concepts such as Master Data Management Data Governance and Enterprise Data Warehouse
• Applying leading practices in supporting high availability, scalable, process and storage intensive solutions architectures to data integration/migration, analytics and insights, AI and ML requirements
• Understanding and familiarity of one or more is a big plus
• CI/CD, cloud devops, containers (Kubernetes/Docker, etc.)
• Understanding of insurance data, underlying KPIs and how they are used
• Demonstrating prior P&C/L&A Insurance industry experience.

Tech Stack

• Amazon Redshift
• AWS
• Azure
• BigQuery
• Cloud
• Cognos
• Docker
• ETL
• Google Cloud Platform
• Hadoop
• Kafka
• Kubernetes
• Matillion
• Python
• Scala
• Spark
• SQL
• SSIS
• Tableau
• Terraform
• Vault

Benefits

• Health insurance
• Dental insurance
• Vision insurance
• 401(k)
• Paid time off
• Vacation
• Sick leave
• Family sick leave
• Annual discretionary bonus