Principal Data Engineer - Global Cybersecurity Data & Analytics

Liberty Mutual Insurance•Boston, MA

1d•$120,000 - $225,000

About The Position

The Global Cybersecurity Data and Analytics team is seeking an innovative, collaborative Principal Data Engineer to help build and grow our Data and Analytics practice. As a member of the team, you will play a crucial role in delivering innovative data-driven solutions that enhance our organization's cybersecurity posture. Under general direction, acts as a technical expert who consults on highly complex projects. Responsible for the analysis, development, and execution of complex data solutions, to manage the information lifecycle needs of an organization. Collects, integrates, and analyzes data with the purpose of drawing conclusions about that information. Develops, constructs, tests, and maintains data architectures for data platforms, databases, analytical/reporting, or data science systems. Establishes and builds data systems including providing standards, policies, practice, procedures, governance, and quality assurance for data deliverables. Recommends methods to improve data reliability, quality, and efficiency. Devises or modifies procedures to solve technical problems. Leads and directs the work of team members. May mentor junior team members.

Requirements

Bachelor's or Master's degree in a technical or business discipline or equivalent experience, technical degree preferred
Generally, 8+ years of professional experience
In-depth knowledge of IT concepts, strategies, and methodologies
In-depth knowledge of diverse and emerging technologies and new architectural concepts and principles
Knowledgeable in data engineering languages and tools; proficient in new and emerging technologies
In-depth understanding of layered solutions and designs; in-depth understanding of shared data engineering concepts and product features, as well as security minded
In-depth knowledge of business operations, objectives, and strategies; in-depth understanding of global business and technology trends and the financial services industry
Highly developed negotiation, consensus building & influencing skills, facilitation, and adaptability to respond to change quickly
Highly developed oral and written communication skills; strong presentation skills
Ability to effectively collaborate with all levels of the organization
Solid Python Pandas and SQL programming skills with analytical and critical thinking skills with an understanding of big data technology
An understanding of machine learning principles, statistics and algorithms.
Understanding of Data Warehouse solutions, modeling and governance

Nice To Haves

Working knowledge of AWS, Azure and GCP cloud environments
Power BI development (DAX and M query) and Power BI gateway
Snowflake administration experience
AWS Airflow
History of working with ETL (extract, transfer and load) and data pipeline technology
Proven experience in data modeling, governance and analytics
Ability to leverage and build APIs
Python programming knowledge
SQL query and data management

Responsibilities

Consults on designing and developing complex programs and tools to support ingestion, curation, and provisioning of complex enterprise data to achieve analytics, reporting, and data science.
Builds and designs data architecture that improve accessibility, efficiency, governance, and quality of data.
Collects, cleans, and transforms traditional and big data to ensure data accuracy and accessibility.
Makes recommendations for how to improve data and drives those recommendations forward.
Builds in-depth knowledge of technology enablers.
Documents existing processes, organizational structures, architectures, and external systems.
Contributes to the development and enhancement of solutions for key business outcomes.
Develops interactive and visually appealing data visualizations of large amounts of data to reveal patterns, trends, or correlations.
Provides guidance on capabilities and functionalities of Power BI visualization tools.
Presents to, and educates, a wide range of people on using visualizations.
Actively uses AI tools to improve the speed, quality, and scale of work; can point to concrete workflows where AI adds value; critically evaluates and validates AI-generated output; and applies AI responsibly, protecting confidential and customer data.