Harman

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 serve as the critical link between global business automotive operations and scalable data platform execution. Your primary focus will be translating complex operational needs into robust, reusable data pipelines that power analytics, BI, and AI use cases.

What You Will Do

You will act as a full-stack data engineer, working across the lifecycle of data—ingestion, transformation, modeling, and delivery. Unlike role-specific analytics development, your solutions will serve multiple downstream consumers, requiring a strong focus on scalability, reliability, and reusability.

This role requires a hybrid mindset: deep understanding of business processes in Manufacturing, Procurement, and SCM, combined with strong engineering discipline to build high-performance, production-grade data pipelines.

1. Business Analysis & Requirements Translation

• Stakeholder Partnership:

• Work with business users, analysts, and developers to understand data requirements across multiple use cases.

• Technical Translation:

• Translate business needs into scalable data models, pipeline logic, and data integration requirements.

• Process Alignment:

• Develop a deep understanding of operational workflows to ensure that data pipelines accurately represent business processes and can support diverse analytical needs.

2. Data Pipeline Design & Development

• Pipeline Design:

• Design and implement scalable data pipelines for ingestion, transformation, and delivery of data across multiple domains.

• Reusability & Scalability:

• Build pipelines that serve multiple consumers (BI, AI, data products), ensuring flexibility and extensibility.

• Performance Optimization:

• Optimize data processing for large-scale datasets, ensuring efficient and reliable execution.

3. Data Engineering & Modeling

• SQL & Data Transformation:

• Write efficient SQL queries, transformations, and data processing logic to structure data for downstream consumption.

• Data Modeling:

• Design and maintain data models aligned with enterprise standards (e.g., layered/medallion architecture).

• Data Product Enablement:

• Develop and contribute to shared, governed data products that act as single sources of truth across the organization.

• Data Quality:

• Implement validation, testing, and monitoring to ensure data accuracy, consistency, and reliability at scale.

4. Deployment & Lifecycle Management

• Promotion & Release:

• Manage deployment of pipelines and data solutions across Dev → QA → Production environments, ensuring stability and reliability.

• Source Control:

• Use Git to manage pipeline code, configurations, and versioning following team standards.

• Monitoring & Maintenance:

• Monitor pipeline performance, troubleshoot failures, and continuously improve reliability and efficiency.

5. Collaboration & Standards

• Team Alignment:

• Work closely with the System Architect to ensure pipelines align with architectural patterns, scalability requirements, and security standards.

• Cross-Functional Collaboration:

• Enable downstream teams (BI, AI, analytics) by delivering high-quality, well-structured data.

• Peer Review:

• Participate in code reviews to ensure consistency, maintainability, and adherence to best practices.

6. AI-Assisted Development & Automation

• AI-Assisted Coding:

• Use AI tools to accelerate development of data pipelines, transformations, and documentation.

• Automation:

• Automate repetitive data engineering tasks such as data validation, transformation generation, and pipeline monitoring.

• Continuous Upskilling:

• Develop expertise in modern data engineering practices, including distributed processing and AI-enabled workflows.

What Success Looks Like

• Data pipelines are robust, scalable, and reusable across multiple use cases

• Data products provide consistent, trusted, and governed data

• Systems handle large volumes of data efficiently and reliably

• Downstream teams (BI, AI) can build faster using high-quality data foundations

• Data issues are proactively identified and resolved

What You Need to Be Successful

• Strong SQL and data transformation skills

• Experience with data pipelines and ETL/ELT frameworks

• Understanding of data modeling and layered architectures (e.g., Medallion)

• Experience with large-scale data processing (e.g., Spark, Databricks) is a plus

• Familiarity with cloud platforms (AWS, Azure) is a plus

• Experience with Git and modern development practices

• Strong problem-solving and performance optimization skills

• Understanding of APIs and data integration patterns

• Working knowledge of Python for data processing, automation, and pipeline development

Bonus Points if You Have

• Experience with Databricks, Spark, or distributed data processing frameworks

• Experience working with cloud platforms such as Azure or AWS

• Experience building data pipelines using Python

• Familiarity with Delta Lake, Medallion Architecture, or modern Lakehouse concepts

• Experience working with manufacturing, supply chain, procurement, or operational data

• Exposure to BI and analytics tools such as Power BI, Qlik, Tableau, or similar platforms

• Familiarity with REST APIs, JSON, and integrating external data sources

• Experience using AI-assisted development tools such as GitHub Copilot, ChatGPT, or similar coding assistants

• Understanding of data quality, validation, and testing concepts

• Experience with Agile development methodologies and collaborative software development practices

• Bachelor's degree in Computer Science, Information Systems, Engineering, Data Analytics, or a related field

What we offer 

• Work in international teams with the world’s largest automotive manufacturers.

• Use HARMAN Flex – choose the right working model fitting their job (Hybrid or Office)

• Access career development opportunities and get both on the job training on high-end automotive projects, as well as extensive technical trainings.

• Access HARMAN Webshop with large employee discounts for audio products (JBL, HARMAN Kardon, AKG)

• Are encouraged to a healthy work/life balance with a progressive holiday plan based on total work experience, 2 sick days, 3 days off compensation for weekend legal holidays and flextime.

• And of course, enjoy meal tickets, a premium medical subscription, fitness discounts and other corporate perks.

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