Prinicipal, Data Engineer

Mercedes-Benz Vans USA

Atlanta (GA)

On-site

USD 140,000 - 200,000

Full time

6 days ago

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Benefits offered by this job

Mobile working possible

Employee events

Health measures

Pension plan

Mobility benefits

Flexible working hours

Employee discounts

Coaching

Employee participation possible

Parking

Good transport links

Accessibility

Childcare

Canteen, Café

Job summary

Mercedes-Benz USA sucht einen Principal Data Engineer, der als technischer Lead für unternehmensweite Dateninitiativen fungiert. Sie definieren Architekturen, Standards und liefern skalierbare Data-Plattformen für Reporting, Analytics und ML.

Sie arbeiten in einer schnelllebigen, kollaborativen Umgebung, führen Cross-Functional Teams und etablieren Best Practices in DataOps, Monitoring und Governance, um Geschäftseinblicke zu ermöglichen.

Qualifications

Bachelor-Abschluss in Informatik, Engineering, Data Science, Informationssysteme oder vergleichbare praktische Erfahrung.
8+ Jahre progressive Erfahrung in Data Engineering, Software Engineering oder ähnlichen technischen Bereichen.
Nachweisbare Erfahrung im Entwerfen, Aufbau und Betrieb von Enterprise-Datenplattformen oder geteilten Engineering-Fähigkeiten.
Fähigkeit, mehrdeutige Probleme zu definieren, Stakeholdern zu alignen und outcomes zu liefern.

Responsibilities

Entwicklung und Weiterentwicklung der Architektur, Muster, Standards und Best Practices für Data-Plattformen.
Entwurf und Lieferung leistungsfähiger, skalierbarer Data-Plattformen und -Produkte für Analytics, Reporting, ML/AI.
Zusammenarbeit mit Data-Engineering-, Analytik- und Produktteams zur Bereitstellung zuverlässiger Dienste.

Skills

Python

SQL

PySpark/Scala

Azure Databricks

Delta Lake

CI/CD

Docker/Kubernetes

DevOps/DataOps

Observability/Monitoring

Data governance

Education

Bachelor-Abschluss in Informatik/Engineering/DS

Tools

Azure

Azure Databricks

Delta Lake

Power BI/Tableau

Job description

About Us

Mercedes-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.

Aufgaben

Job Overview

Do 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.

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.

Qualifikationen

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