Principle Data Engineering - Enterprise Platform

A Career at HARMAN

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As a technology leader that is rapidly on the move, HARMAN is filled with people who are focused on making life better. Innovation, inclusivity and teamwork are a part of our DNA. When you add that to the challenges we take on and solve together, you’ll discover that at HARMAN you can grow, make a difference and be proud of the work you do every day.

Introduction: A Career at HARMAN Automotive

We’re a global, multi-disciplinary team that’s putting the innovative power of technology to work and transforming tomorrow. At HARMAN Automotive, we give you the keys to fast-track your career.

• Engineer audio systems and integrated technology platforms that augment the driving experience
• Combine ingenuity, in-depth research, and a spirit of collaboration with design and engineering excellence
• Advance in-vehicle infotainment, safety, efficiency, and enjoyment

About the Role

As a Data Engineer, you will be a highly experienced individual contributor responsible for the design and delivery of complex, production-scale data products on HARMAN Automotive's enterprise data and AI platform. You will provide technical leadership across data engineering initiatives, solve difficult cross-domain problems, and help establish reusable engineering patterns for teams across the organization. This role combines deep Azure Databricks and data engineering expertise with technical leadership, mentoring, and close collaboration across business and technology teams.

What You Will Do

• Lead the technical design and delivery of complex and cross-domain data products using Azure Databricks and the enterprise data platform.

• Design scalable data pipelines, transformation architectures, data models, and integration patterns for high-value business use cases.

• Make technical decisions and resolve complex engineering, performance, data quality, and integration challenges.

• Lead engineers in applying strong software and data engineering practices, including CI/CD, automated testing, observability, code review, and deployment automation.

• Define and improve reusable data engineering patterns, templates, and golden paths in partnership with Platform Engineering.

• Provide technical guidance and mentoring to other Data Engineers while remaining hands-on with critical engineering work.

• Partner with architects, Platform Engineering, security, MDM/Data Quality, Analytics, and domain teams to ensure data products meet enterprise standards.

• Guide the implementation of data contracts, quality controls, lineage, metadata, security, and operational requirements within data products.