Data & analytics architect (Santiago de Querétaro)

We're a general, multi-disciplinary team that’s putting the innovative power of technology to work and transforming tomorrow. Engineer intelligent systems and data-driven solutions that enhance personalization and entertainment as part of the in‑cabin experience.

Combine research, experimentation, and collaboration across multiple engineering disciplines. Advance analytics and machine learning capabilities that power next‑generation automotive solutions.

Responsibilities

• Design and build an end‑to‑end audio data collection and consumption platform that enables advanced analytics, audio information retrieval, and personalization across the Car Audio Division.
• Establish standardized, secure, and scalable pipelines to collect, curate, and govern data from internal engineering systems, companion apps, and connected‑vehicle telemetry.
• 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.
• 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.
• 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 with quality guardrails (schema validation, anomaly detection, etc.).
• Develop and maintain data lakes and lakehouse architectures.
• Design and implement a 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 Engineers and Data Scientists to optimize data formats for training performance and storage efficiency.
• Design cost‑aware policies for data retention, sampling, compression, and technology selection.
• Establish measurable KPIs for data cost efficiency, pipeline reliability, and performance.
• Mentor other engineers on practical data engineering, performance tuning, and cost‑efficient design.
• Strong execution mindset with the ability to design, implement, debug, and optimize data systems end‑to‑end.

Qualifications

• 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.
• Experience working with audio, image, or signal processing domains.
• Background working with automotive datasets or connected‑vehicle data.
• Experience deploying ML models to production (cloud or edge environments).
• Experience with event‑driven architectures (Kafka‑like patterns, IoT ingestion patterns).
• Experience programming with C++ and embedded systems.
• Experience building reproducible working environments (Docker, virtual environments).
• Advanced English communication skill; will be part of a global team.

Benefits

• Willing to work in an office at Queretaro as part of hybrid flex work.
• Flexible work environment.
• Extensive training opportunities through our own HARMAN University.
• An inclusive and diverse work environment that fosters and encourages professional and personal development.

We proudly offer added opportunities for training, development, and continuing education, further empowering you to live the career you want.

All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. HARMAN attracts, hires, and develops employees based on merit, qualifications and job‑related performance.