Data Analytics Consultant

Job Summary

The Data Engineering Consultant, working independently under limited oversight, empowers the organization through architecting, designing, and executing advanced analytics capabilities. In an agile team setting, they collaborate with data scientists, data analysts, and product teams to translate business needs into technical specifications and develop complex data pipelines. This role sets the strategic and technical direction for data capabilities, designing pipelines for data extraction, transformation, and loading from diverse sources. They handle large, complex data sets, solve business challenges using unstructured data, and act as a subject matter expert, mentoring less experienced Data Engineers. The focus of this role within the exposure engineering team is the build out of data products that integrate exposure data and modelled-loss outputs, and the publishing of certified datasets and dashboards that enable the business to visualize and manage its enterprise exposures in line with risk appetite.

Job Responsibilities

• Responsible for designing, maintaining and implementing the overall strategic vision for acquisition, storage and consumption of data, particularly in their specific area of focus in collaboration with other technical leads, Solution Architects, Enterprise Architects and Security/Risk/Audit resources.
• Responsible for building technical roadmaps that contain long-term design that are securely engineered to provide or support high quality data services to the business.
• Designs and builds solutions based on strategic vision, user needs, best practices, and tool capabilities in collaboration with business stakeholders, IT resources and Architects.
• Assists with preparing and reviewing estimates and distributing work across the team, including enhancements, production support and on-call responsibilities.
• Helps develop talent and build effective teams through coaching, mentoring, feedback and training.
• Designs, builds, and maintains custom data pipelines and ETL processes in support of business and Data Scientist needs and initiatives.
• Populates data warehouses, and data marts to meet demand for data across the organization using traditional data integration technologies including, ETL, and data replication/CDC.
• Builds and maintains API / C# .NET connectors for model vendor integrations
• Enables data consumption via visualization tools and underpinning semantic models (e.g. PowerBI)
• Implements geospatial roll-ups for visualization heatmaps (using H3/hex-grid functions)
• Applies loss-modelling business logic for property (catastrophe), casualty and cyber business
• Partners with data analysts, data scientists, and other data consumers across IT and the business to optimize data availability with intention to build, refine and enhance AI/ML models and algorithms.
• Drives continuous improvement in data pipelines and data warehouses and partners with others to ensure both timely availability and security of data.
• Provides on-call support daily operations via analyzing and correcting incidents and defects in a timely fashion.
• Serves as a peer mentor to less experienced Data Engineers.
• Coordinates and directs work assignments.

Job Qualifications

• 7+ years of Data Analyst experience.
• Bachelor’s degree in Information Technology, Computer Science, Engineering, Mathematics or related field or commensurate experience.
• Experience in P&C (re)insurance risk analytics with cat-modelling exposure/results data familiarity (AIR/RMS)

Behavioral Competencies

• Collaborates
• Communicates Effectively
• Customer Focus
• Decision Quality
• Nimble Learning

Technical Skills

• Snowflake (Streams/tasks, snowpipe, performance tuning)

• SQL

• .NET (C#) API Development (REST, JSON)

• PowerBI

• Data analysis

• Data Modeling

• Data Engineering

• Python

• DevOps

This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management.