Lead Data Engineer - Jersey City, United States - Combined, a Chubb Company

Description

Are you a proven data engineering leader who thrives in a fast-paced environment, demonstrates strong attention to detail and can grow a hardworking team of data engineering professionals?
This is a rare opportunity to apply your leadership and engineering expertise to a subject you love: Data

We need someone to develop people, form strong working partnerships with business and technology leaders, plan and implement data engineering programs, formulate data and analytics strategies for solving business problems.

You'll have superb engineering, technical, business and communication skills to be able to work with functional leaders to define and prioritize key data needs and build data products & platforms.

If you have exceptionally strong cloud data engineering skills, experience implementing complex real-time data and analytics platforms to produce practical insights, then we'd love to hear from you


RESPONSIBILITIES
Develop the vision of the insurance data fabric by defining measurable/concrete objectives and key results for the data engineering chapter to derive transformation of the data ecosystems
Derive innovation and build highly scalable real time data pipelines and data platforms to support the business needs
Build a data engineering organization that is business focused, proactive, and resilient
Attract, hire and retain top engineering talent, creating an engineering culture that fosters innovation and collaboration
Promote data governance and master/reference data management as a strategic discipline
Implement strategies to monitor the effectiveness of data management
Drive mediatization of the data capabilities that anticipate changes in the strategic business imperatives
Be an inspiring engineering leader, mentor and coach data engineers and be an active member of the data leadership team
Evaluate emerging data technologies and determine their business benefits and impact on the future-state data platform

EDUCATION AND EXPERIENCE
Proven experience in large multinational financial services industry
Have previously held a data engineering leadership role
Candidate should have in-depth experience in designing and implementing enterprise-wide cloud data and analytics platforms
Have hands-on architecture and delivery experience in large scale, cloud data management solutions. Strong preference to Azure and DataBricks experience
Hands-on experience architecting and implementing large scale multi discipline master/reference data management, cloud data lake and analytics platforms
Data technology literate with a detailed understanding of the modem data architectures and data analytics platforms
Presentation and facilitation and design-thinking skills
Insurance business domain, data/content and process understanding
Knowledge of relational/object modelling, knowledge/graph modelling techniques
Understanding of metamodels, taxonomies and ontologies
Ability to assess rapidly changing technologies and apply them to business needs

KEY BEHAVIORS AND COMPETENCIES
Ability to work well with others and be respected as a leader
Track record of remaining unbiased toward specific technologies or vendors
Deep understanding of agile project delivery models and methodologies
Excellent communication skills both verbal and written that clearly and concisely communicates concepts to varying levels of the organization
Energetic, self-starter who can independently multi-task across many different complex strategic programs to drive multiple deliverables concurrently
Creative problem solver with the ability to quickly identify and resolve errors through collaborative solutions
Data-driven decision maker; able to complete thorough research and investigation, yet quickly make decisions and present findings
Capable of working collaboratively with leaders and business partners
Understanding of analytics applications and processes
Experience working across business, technical, IT, Digital and Operations teams to influence decisions and drive outcomes

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