Data Engineer transforming data for analysis in an insurance company. Responsible for building data infrastructures and optimizing data delivery.
Responsibilities
Build the infrastructure required for optimal extraction and transformation from a wide variety of data sources.
Build and optimize ‘big data’ pipelines, architectures, and datasets to be used across the organization.
Understand and translate complex business priorities into clearly defined technical/data specifications for implementation.
Support other team members on data initiatives and ensure optimal data delivery architecture consistency throughout ongoing projects.
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Implement processes and systems by coding, testing, and debugging to monitor data quality, and ensure accuracy of production data.
Collaborate with analytics and business teams to improve data models that feed business intelligence tools to increase data accessibility and fostering data-driven decision making across the organization.
Work closely with business architecture, IT, and analytic teams to help implement an end-to-end data strategy from data ingest to output into business tools.
Work with Modeling Analyst to data mine and extract key identifiers coming from unstructured, free format datasets.
Collaborate across multiple business functions to combine several aspects (such as rating and competition) of predictive modeling results into one analytical dashboard.
Expand knowledge in multiple programming languages and software.
Monitor developments in data transformation and storage to remain current with respect to new approaches and methods utilized within the data science industry.
Complete internal and external coursework to further develop programming skills and business knowledge.
Other duties as assigned.
Requirements
Bachelor’s degree in computer science, statistics, math, or related field or equivalent combination of education and experience.
2 years of experience in a data science and/or programming related field.
Work experience with relational databases and query authoring.
Experience supporting and working with cross-functional teams in a dynamic environment.
Experience developing data pipelines for warehouses/lakes.
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