Data Platform Engineer

harman; Santiago de Querétaro; Presencial; MXN 420.000 - 660.000; Jornada completa

Descripción de la vacante

HARMAN Automotive is seeking a Data Engineer on the Innovation Team to design and build an end-to-end audio data platform, enabling advanced analytics, audio information retrieval and personalization across Car Audio Division.

You will establish standardized, secure, and scalable pipelines to collect, curate, and govern data from internal engineering systems and connected-vehicle telemetry, collaborating with Data Scientists, ML Engineers, Embedded/DSP Engineers and Audio Experts to ensure

Formación

• 5+ years of hands-on experience building and operating large-scale data pipelines and platforms.

Responsabilidades

• Design and implement standardized data ingestion frameworks for batch and streaming sources (internal databases, user-preference data, vehicle telemetry).
• Define and maintain data models and data contracts (schemas, semantics, versioning rules) for audio-related files, user preferences and metadata including quality guardrails (schema validation, anomaly detection, etc.).
• Develop and maintain data lakes / lakehouse architectures
• Design and implement standardized API for data consumption.
• Prepare and curate high-quality datasets for AI/ML model training, validation, experimentation and statistical analysis.
• Collaborate directly with ML Engineer and Data Scientist to optimize data formats for training performance and storage efficiency
• Design cost-aware policies for data retention, sampling, compression, and technology selection
• Optimize pipeline execution times and resource usage (batch vs streaming, compute sizing, caching strategies)
• Establish measurable KPIs for data cost efficiency, pipeline reliability, and performance
• Ensure compliance with internal policies, OEM requirements, and regulatory constraints
• Create clear documentation for pipelines, schemas, and architectural decisions
• Mentor other engineers on practical data engineering, performance tuning, and cost-efficient design

Conocimientos

Python

PySpark

SQL

Data pipelines

Cloud platforms

Data governance

Privacy by design

Data modeling

Team collaboration

Educación

Bachelor's or Master's degree in Computer Science, Data Engineering, Software Engineering

Herramientas

AWS S3

Azure

Databricks

Lakehouse

Descripción del empleo

HARMAN's engineers and designers are creative, purposeful and agile. As part of this team, you'll combine your technical expertise with innovative ideas to help drive cutting‑edge solutions in the car, enterprise and connected ecosystem. Every day, you will push the boundaries of creative design, and HARMAN is committed to providing you with the opportunities, innovative technologies and resources to build a successful career.

A Career at HARMAN

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 everyday.

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 intelligent systems and data‑driven solutions that enhance personalization and entertainment as part of in‑cabin experience
• Combine research, experimentation, and collaboration across multiple engineering disciplines
• Advance analytics and machine learning capabilities that power next generation automotive solutions

About the Role

As a Data Engineer on the Innovation Team, you will design and build an end‑to‑end audio data collection and consumption platform that enables advanced analytics, audio information retrieval, and personalization capabilities across Car Audio Division.

You will establish standardized, secure, and scalable pipelines to collect, curate, and govern data from internal engineering systems, companion apps, and connected‑vehicle telemetry. You will collaborate closely with Data Scientists, ML Engineers, Embedded/DSP Engineers, and Audio Experts to ensure high‑quality data products are consistently available for experimentation, training, validation, analysis, and production monitoring-while meeting strict privacy, security, reliability, and automotive compliance requirements.

You will also serve as a platform consultant, advising other departments on data architecture, data contracts, ingestion design, and downstream consumption, while adhering to strict privacy, safety, and reliability requirements.

What You Will Do

• Design and implement standardized data ingestion frameworks for batch and streaming sources (internal databases, user‑preference data, vehicle telemetry).
• Define and maintain data models and data contracts (schemas, semantics, versioning rules) for audio‑related files, user preferences and metadata including quality guardrails (schema validation, anomaly detection, etc.).
• Develop and maintain data lakes / lakehouse architectures
• Design and implement standardized API for data consumption.
• Prepare and curate high‑quality datasets for AI/ML model training, validation, experimentation and statistical analysis.
• Collaborate directly with ML Engineer and Data Scientist to optimize data formats for training performance and storage efficiency
• Design cost‑aware policies for data retention, sampling, compression, and technology selection
• Optimize pipeline execution times and resource usage (batch vs streaming, compute sizing, caching strategies)
• Establish measurable KPIs for data cost efficiency, pipeline reliability, and performance
• Ensure compliance with internal policies, OEM requirements, and regulatory constraints
• Create clear documentation for pipelines, schemas, and architectural decisions
• Mentor other engineers on practical data engineering, performance tuning, and cost‑efficient design

What You Need to Be Successful

• Strong execution mindset with the ability to design, implement, debug, and optimize data systems end‑to‑end
• Bachelor's or Master's degree in Computer Science, Data Engineering, Software Engineering, or a related field
• 5+ years of hands‑on experience building and operating large‑scale data pipelines and platforms
• Strong proficiency in Python, PySpark and SQL for data processing and automation
• Solid experience with cloud‑based data platforms (e.g., AWS S3, Azure, Databricks, object storage, distributed computing)
• Proven ability to automate repetitive tasks and improve data hygiene
• Proven experience implementing cost‑saving strategies in data platforms (storage tiering, compute optimization, pipeline tuning)
• Deep understanding of data modeling, partitioning, indexing, and performance optimization
• Experience handling large‑volume, high‑frequency or unstructured data (audio, signals, logs, telemetry)
• Strong knowledge of data governance, and privacy best practices
• Working knowledge of privacy‑preserving data handling (pseudonymization, anonymization, etc.), data‑quality checks, and data‑lineage tracking.
• Ability to work independently and collaborate effectively in cross‑functional global teams
• Strong communic