Data Senior Engineer

Westfield•Westfield Center, OH

31d

About The Position

A Senior Data Engineer has direct impact on important initiatives that enable our business by architecting, designing, and implementing advanced analytics capabilities. Working in an agile team environment and without direct supervision, the Senior Data Engineer collaborates with data scientists, data analysts, product teams, and other stakeholders to translate business requirements to technical specifications and coded data pipelines. 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.

Requirements

5+ years of Data Engineering experience or related experience.
Bachelor’s degree in Information Technology, Computer Science, Engineering, Mathematics or related field or commensurate experience.
SQL
Snowflake (Streams/tasks, snowpipe, performance tuning)
.NET (C#) API Development (REST, JSON)
PowerBI
Data analysis
Data Engineering
Python
Data Modeling

Nice To Haves

Experience in P&C (re)insurance risk analytics with cat-modelling exposure/results data familiarity (AIR/RMS) preferred

Responsibilities

Designs, builds, and maintains custom data pipelines for the extraction, transformation, and loading (ETL) of data from a variety of data sources.
Populate data warehouses, 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.
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 for daily operations via analyzing and correcting incidents and defects in a timely fashion.
Navigates existing data stores, handles large and complex data sets and uses unstructured data to solve business challenges.
Utilizes excellent communication skills, seeks out challenges and has a strong desire to continually improve their knowledge and skills.
Enables data consumption via visualization tools and underpinning semantic models (e.g. PowerBI)
Serves as a peer mentor to less experience Data Engineers.