Vice President Principal Java Software Engineer Jobs in Haddonfield, NJ

By joining Chubb as Principal Data Engineer for our North America Finance & Actuarial and Corporate Data platforms, you'll set the engineering direction for a portfolio of strategic applications that directly underpin financial, actuarial, claims, regulatory, underwriting and executive decision-making across the enterprise. This is a technical leadership role: you'll define and drive engineering standards, architect and implement no-touch data pipelines and integrations, and transform the way our engineering squads deliver by embedding AI-assisted development, modern DevOps practices, and cloud-first design into everything we build. You'll influence and guide a team of data engineers across multiple squads, provide hands-on technical leadership on the most complex initiatives, and serve as the senior engineering voice in cross-functional conversations with architects, platform teams, and business stakeholders.

Responsibilities Include:

• Define and drive the engineering strategy across Finance, Actuarial, and Corporate Data platforms, establishing and enforcing standards, patterns, and best practices across all squads.
• Architect and implement no-touch, automated data pipelines and integrations that minimize manual intervention, reduce operational risk, and improve reliability at scale.
• Lead the adoption of AI-assisted development practices - including AI-augmented code generation, pipeline automation, anomaly detection, and intelligent data quality monitoring - to accelerate delivery and reduce toil.
• Provide hands-on technical leadership on high-complexity initiatives, including cloud migration (Azure Synapse / Databricks / Snowflake), ETL modernization, and replatforming efforts.
• Evaluate and recommend modern tooling, frameworks, and architectural patterns; build the business case and lead adoption across engineering squads.
• Partner with the data reliability engineering and enhancement squad leads to ensure engineering standards are embedded in day-to-day delivery from design through deployment and operations.
• Establish CI/CD pipelines, automated testing frameworks, and deployment standards that enable consistent, high-quality releases across a variety of different data systems and products.
• Lead root cause analysis and resolution for the most complex data engineering issues, driving permanent fixes over tactical workarounds.
• Build, lead, and develop a team of approximately five direct-report senior data engineers and engineering leads across Finance, Actuarial, and Corporate Data squads; drive performance, engineering accountability, and a clear path for career growth.
• Define, govern, and enforce engineering standards and best practices across distributed and offshore engineering teams; hold ultimate accountability for the quality, consistency, and technical direction of engineering products delivered by those teams, regardless of reporting structure.
• Translate complex technical strategies into clear communications for executive stakeholders, including the Head of Data, North America, Head of Data Engineering, North America, and senior business leaders.
• Maintain and evolve technical documentation, architecture decision records, and engineering runbooks as living assets.
• Stay current on emerging data engineering technologies and bring relevant innovations into the team's delivery model.

• Bachelor's degree required in Computer Science, Computer Information Systems, Information Systems, Information Technology, Computer Engineering, or equivalent work experience.
• 12+ years of progressive data engineering experience, including hands-on ETL/ELT development, data warehouse design, and enterprise data pipeline delivery.
• 8+ years of experience with ETL development tools and concepts, with deep expertise in Informatica / IICS, Databricks or other similar technologies.
• 5+ years of experience with cloud data platforms including Azure (Synapse Analytics, Azure Data Factory, Azure Databricks) and Snowflake.
• Strong hands-on proficiency in Databricks (Delta Lake, Spark, notebooks, workflows) and Snowflake (data sharing, Snowpark, dynamic tables).
• 3+ years of experience with job scheduling tools such as Autosys or comparable distributed schedulers.
• 3+ years of scripting experience in Python, Shell, or comparable languages for pipeline automation and tooling.
• Demonstrated ability to architect and deliver no-touch, fully automated data pipelines in an enterprise environment.
• Proven track record of driving engineering transformation: adopting modern practices (CI/CD, infrastructure-as-code, automated testing, AI-assisted tooling) in a large, complex data organization.
• Strong understanding of data warehousing concepts including dimensional modeling, data lineage, data quality frameworks, and enterprise DW architecture.
• People leadership required: must have managed direct-report senior data engineers and/or technical leads.  Demonstrated experience governing distributed and offshore engineering teams required; this role carries ultimate engineering accountability for products delivered by those teams, including standards adherence, quality, and technical direction.
• Excellent communication skills; able to translate engineering complexity into clear, credible language for both technical teams and executive stakeholders.
• Insurance industry experience preferred; P&C domain knowledge (financial reporting, actuarial data, claims, regulatory/bureau reporting) a strong plus.
• Location: must be based in Whitehouse Station or Jersey City, NJ, Philadelphia, PA, or Simsbury, CT.

The pay range for the role is $183,700 to $240,000. The specific offer will depend on an applicant's skills and other factors. This role may also be eligible to participate in a discretionary annual incentive program.  Chubb offers a comprehensive benefits package, more details on which can be found on our careers website.  The disclosed pay range estimate may be adjusted for the applicable geographic differential for the location in which the position is filled.