Principal Data Engineer - United States

Only for registered members United States

3 days ago

$190,000 - $280,000 (USD) per year *

* This salary range is an estimation made by beBee

About Our Client · Our client is a specialized consulting firm dedicated to delivering data and analytics solutions to clients in the Property & Casualty (P&C) insurance industry. Their team is passionate about helping insurers unlock business value through data-driven insights, ...

Job description

About Our Client

Our client is a specialized consulting firm dedicated to delivering data and analytics solutions to clients in the Property & Casualty (P&C) insurance industry. Their team is passionate about helping insurers unlock business value through data-driven insights, modern technology, and strategic execution. As a boutique firm, we combine deep industry expertise with agility, enabling their clients to innovate and solve their most complex business challenges.

Who You'll Work With

As part of our team, you will lead and develop industry-leading data analytics solutions for our clients – while working closely with business users and data owners.

About You

You are passionate about data analytics. You have an entrepreneurial spirit that drives you to tackle new challenges proactively. Your flexibility enables you to adapt to different roles and wear many hats to get the job done. You bring a creative and innovative approach to solving problems, constantly thinking outside the box. As a team player, you enjoy collaborating with others in a close-knit team environment.

What You'll Do

Lead the design and delivery of enterprise-scale data platforms and pipelines supporting batch, micro-batch, and real-time ingestion patterns.
Provide technical leadership to data engineering teams, including solution design reviews, code reviews, and mentoring junior and senior engineers.
Partner with enterprise architects, product owners, and business leaders to translate strategic objectives into scalable data architecture and roadmaps.
Architect high-performance, secure, and cost-efficient data solutions aligned with cloud and data platform best practices.
Design and implement advanced data integration patterns, including streaming, CDC (Change Data Capture), event-driven architectures, and API-based ingestion.
Own end-to-end data lifecycle management, including ingestion, transformation, semantic modeling, data serving, and archival strategies.
Establish and enforce data engineering standards, governance frameworks, and reusable design patterns across the organization.
Drive adoption of DataOps practices, including automated testing, observability, lineage, and proactive monitoring.
Lead performance tuning, cost optimization, and capacity planning initiatives for large-scale data environments.
Guide platform selection, tool evaluation, and modernization efforts (e.g., migration from legacy warehouses to cloud-native architectures).
Collaborate with security and governance teams to ensure regulatory compliance, privacy, and data protection requirements are embedded in solutions.
Act as the technical escalation point for complex production issues and lead root cause analysis.
Influence organizational data strategy and contribute to long-term architecture decisions.
Work cross-functionally with analytics, data science, and AI/ML teams to enable advanced use cases and data products.

Required Qualifications

years of experience in data engineering with demonstrated progression into technical leadership roles.
4+ years of deep expertise with modern cloud data platforms such as Snowflake, Databricks, or equivalent.
Strong hands-on experience designing both real-time and batch data pipelines using technologies such as Kafka, Spark Structured Streaming, Flink, or similar.
Advanced programming skills in Python, Scala, or Java, with expert-level SQL proficiency.
Extensive experience building data solutions on cloud platforms (AWS preferred), including storage, compute, networking, and serverless services.
Proven experience in architecting lakehouse or modern data warehouse architectures.
Deep understanding of data modeling techniques (dimensional, Data Vault, medallion architecture, etc.).
Experience implementing enterprise data governance, data quality frameworks, and metadata management.
Strong background in CI/CD, Infrastructure as Code, and automated deployment frameworks.
Demonstrated ability to lead teams, influence stakeholders, and drive large, cross-functional initiatives.
Exceptional problem-solving skills with the ability to operate effectively in complex, ambiguous environments.
Excellent executive-level communication and stakeholder management skills.
Bachelor's or Master's degree in computer science, engineering, or a related field.
Must be authorized to work for any U.S. company without requiring visa sponsorship/transfer.

Location and Travel:

Candidates can reside anywhere in the U.S. and work remotely; however, must be flexible to travel up to 50% to the client location.

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