Prinicipal Data Engineer

Aufgaben About UsMercedes-Benz USA is responsible for the marketing sales and service of Mercedes-Benz and Maybach products in the United States. In our people you will find tremendous commitment to our corporate values. Our products and employees reflect this dedication. We are looking for diverse top-notch individuals to join the Mercedes-Benz team and uphold these hallmarks.Job OverviewDo you love building and pioneering in the technology space Do you enjoy solving complex business problems in a fast-paced collaborative inclusive and iterative delivery environment At Mercedes-Benz USA you will be part of a group that solves real business and customer problems using data.We are seeking a Principal Data Engineer to serve as a senior technical leader for enterprise data engineering. This role defines complex problem spaces sets architectural direction and delivers scalable enterprise-grade data platforms and products that enable reporting analytics machine learning AI products and digital business capabilities. The Principal Data Engineer operates effectively in high-ambiguity environments owns outcomes and business impact and establishes standards frameworks and reusable engineering patterns adopted across multiple teams and domains.ResponsibilitiesEnterprise 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 CICD 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 AIML 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 & ToolsRequired•Deep expertise in Python SQL PySpark andor 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 CICD workflow orchestration Git-based development automated testing and production release practices.•Experience with Docker Kubernetes Infrastructure as Code cloud-native deployment patterns and modern DevOpsDataOps 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. Qualifikationen •Bachelors 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 hourswork 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 StatementMercedes-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.