Principal, Data Engineer

Responsibilities

Enterprise Data Engineering Architecture & Standards

• Define and evolve enterprise data engineering architecture, design patterns, standards, and best practices across data platforms and products.
• Create reusable engineering frameworks, templates, automation standards, and playbooks that accelerate delivery and improve consistency across teams.
• Influence technology choices for data platforms, cloud-native services, distributed processing, orchestration, CI/CD, monitoring, and reliability engineering.
• Evaluate emerging data engineering and platform technologies that improve scalability, performance, security, cost efficiency, and developer productivity.

Data Platform & Product Delivery

• Design and deliver high-performance, scalable data platforms and data products supporting analytics, reporting, machine learning, AI, and enterprise decision-making use cases.
• Build and modernize end-to-end data pipelines across data lake, warehouse, lakehouse, data mart, and semantic consumption layers.
• Enable data engineers, analysts, data scientists, AI engineers, and business teams through reliable, governed, and reusable data services.
• Support platform capabilities for batch, streaming, event-driven, and API-based data integration patterns.

Operational Excellence, Reliability & Governance

• Identify systemic gaps in data quality, platform reliability, observability, performance, cost, resiliency, and operational readiness, and drive solutions end-to-end.
• Establish best practices for production operations, monitoring, logging, incident response, runbooks, platform support, and continuous improvement.
• Ensure platforms and data products comply with enterprise standards for security, governance, data quality, privacy, and responsible data use.
• Drive automation through metadata management, reusable components, and repeatable engineering practices to reduce manual effort and operational risk.

Collaboration, Influence & Technical Leadership

• Partner with architects, infrastructure, security, analytics, AI/ML, product, and business stakeholders to translate complex business needs into scalable technical solutions.
• Operate in high ambiguity by defining problem statements, success metrics, technical options, trade-offs, and implementation approaches.
• Provide technical mentorship and guidance to engineers, raising data engineering maturity and strengthening engineering excellence across the organization.
• Lead cross-functional technical alignment and influence decisions without relying on formal reporting authority.

Technical Skills & Tools

Required

• Deep expertise in Python, SQL, PySpark and/or Scala, and distributed data processing frameworks.
• Strong experience with Azure cloud platforms and Azure Databricks, including Delta Lake and platform-scale data processing patterns.
• Experience designing and operating data lakehouse, warehouse, data mart, semantic layer, and enterprise analytical data products.
• Experience with CI/CD, workflow orchestration, Git-based development, automated testing, and production release practices.
• Experience with Docker, Kubernetes, Infrastructure as Code, cloud-native deployment patterns, and modern DevOps/DataOps practices.
• Strong understanding of observability, monitoring, logging, performance optimization, reliability engineering, and cost management.
• Knowledge of data governance, data quality, data security, access controls, metadata management, and compliance-sensitive environments.

Preferred

• Experience with streaming technologies, event-driven architectures, message queues, and real-time data integration patterns.
• Familiarity with BI and analytics tools such as Power BI, Tableau, Qlik, or comparable semantic-layer-based data discovery platforms.
• Experience with generative AI, agent-based solutions, vector databases, retrieval technologies, or enterprise AI platforms.
• Experience operating in large-scale enterprise environments with multiple business domains and partner teams.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related technical field, or equivalent practical experience.
• 8+ years of progressive experience in data engineering, software engineering, platform engineering, machine learning engineering, or related technical disciplines.
• Demonstrated experience designing, building, and operating enterprise-scale data platforms, data products, or shared engineering capabilities.
• Proven ability to define ambiguous problems, align stakeholders, make technical trade-offs, and deliver outcomes across teams.
• Strong communication, collaboration, stakeholder management, and technical leadership skills.
• Self-starter with strong ownership mindset, sound judgment, and the ability to mentor engineers and influence engineering direction.

Additional Information

• Must be able to work flexible hours/work schedule.
• Travel domestically and internationally as needed.
• Work holidays and weekends when required.
• Position requires collaboration with business, technology, and external partner teams across multiple time zones.
• Enjoys collaborative work and technical mentoring with peers and junior team members.

EEO Statement

Mercedes-Benz USA is committed to fostering an inclusive environment that appreciates and leverages the diversity of our team. We provide equal employment opportunity (EEO) to all qualified applicants and employees without regard to race, color, ethnicity, gender, age, national origin, religion, marital status, veteran status, physical or other disability, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local law.

Benefits

• Mitarbeiterhandy möglich
• Mitarbeiter Events
• Gesundheitsmaßnahmen
• Betriebliche Altersversorgung
• Mobilitätsangebote
• Flexible Arbeitszeit möglich
• Mitarbeiterrabatte möglich
• Coaching
• Mitarbeiterbeteiligung möglich
• Parkplatz
• Gute Anbindung
• Barrierefreiheit
• Kinderbetreuung
• Kantine, Café

Contact

Mercedes-Benz USA, LLC

One Mercedes-Benz Drive 30328 Atlanta