Principal Engineer Data

Principal Data Engineer

The Principal Data Engineer is responsible for architecting and delivering the enterprise data foundation that supports high-volume, real-time data streaming, governed analytics, and AI/ML enablement. You will design and implement scalable pipelines and reusable design patterns, embedding data lineage and governance into every layer to ensure transparency, trust, and reusability across the organization.

This role requires deep expertise in distributed data systems, streaming architectures, and enterprise-scale engineering. You will set technical direction, mentor senior engineers, and ensure the platform achieves performance, reliability, and evolvability at global scale.

Position Responsibilities

• Define the target-state architecture for a unified, cloud-native data foundation and translate business goals into actionable roadmaps.
• Architect and optimize real-time ingestion pipelines capable of handling massive event streams with zero data loss.
• Build reusable, resilient, and scalable pipelines for ingestion, transformation, and analytics across multiple business domains.
• Implement frameworks for end-to-end lineage, metadata management, and governance to ensure data is traceable, high-quality, and reusable.
• Lead the transition from legacy data systems to modern cloud-native architectures with minimal disruption and maximum scalability.
• Establish engineering standards for data modeling, pipeline reliability, observability, and performance optimization at enterprise scale.
• Partner with product, backend, cloud/SRE, and AI/ML teams to ensure cohesive platform evolution.
• Guide senior engineers, promote reusable patterns, and foster a culture of excellence in enterprise data engineering.
• Perform other duties as assigned.

Skills & Qualifications

• 10+ years in data engineering or enterprise data architecture, with 5+ years at principal or staff scope.
• Proven expertise in cloud-native data platforms (Azure, AWS, or GCP) and distributed systems.
• Deep knowledge of Databricks, Spark, Kafka, Flink, and lakehouse architectures.
• Strong background in data lineage, governance, metadata management, and streaming design patterns.
• Experience leading large-scale data streaming and modernization initiatives at enterprise level.
• Ability to influence executives and guide senior engineers across multiple teams.
• Exceptional communication skills-able to simplify complex data concepts for technical and non-technical stakeholders.

Working Conditions

• Work is primarily sedentary and requires frequent use of a computer, keyboard, and mouse.

Please note that this Job Description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.

Under the Americans with Disabilities Act (ADA), WIS is committed to providing reasonable accommodations to qualified individuals with disabilities to enable them to effectively perform the essential functions of the job.