IT Data Engineer

%3Cp style=%22font-family:Arial;%22%3E%3Cspan style=%22background-color:white;color:black;font-family:Calibri,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22line-height:normal;%22%3E%3Cstrong%3EAbout Us%3C/strong%3E%3C/span%3E%3C/span%3E%3C/p%3E%3Cp style=%22font-family:Arial;%22%3E%3Cspan style=%22background-color:white;color:black;font-family:Calibri,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22line-height:normal;%22%3EMercedes-Benz USA is responsible for Marketing, Sales and Service of all 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.%3C/span%3E%3C/span%3E%3C/p%3E%3Cp style=%22font-family:Arial;%22%3E%26nbsp;%3C/p%3E%3Cp style=%22font-family:Arial;%22%3E%3Cspan style=%22background-color:white;font-family:Calibri,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22border:1.0pt none windowtext;line-height:15.0pt;padding:0in;vertical-align:baseline;%22%3E%3Cstrong%3EJob Overview%3C/strong%3E%3C/span%3E%3C/span%3E%3C/p%3E%3Cp%3EDo 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%27ll be part of a group who love to solve real problems and meet real customer needs.%3C/p%3E%3Cp%3EWe are seeking an experienced Senior Data Engineer who will be part of a team building a robust data platform enabling end-to-end capabilities for Reporting, Machine Learning, Generative AI, and Agent-based AI products supporting a variety of users including data engineers, analysts, scientists, AI engineers, and internal/external business partners.%3C/p%3E%3Cp%3EThe Principal Data Engineer is a senior technical leader responsible for defining complex problem spaces, setting architectural direction, and delivering scalable, enterprise-grade data platforms and products. This role operates effectively in high-ambiguity environments, owns outcomes and business impact, and establishes standards and frameworks adopted across multiple teams and domains. The Principal DE plays a critical role in bridging traditional data engineering with modern AI/GenAI data infrastructure, ensuring the data platform evolves to serve both analytics and AI workloads at enterprise scale.%3Cbr%3E%3Cbr%3E%26nbsp;%3C/p%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3EResponsibilities%3C/strong%3E%3C/p%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3EData Platform Architecture %26amp; Engineering (40%)%3C/strong%3E%3C/p%3E%3Cul%3E%3Cli%3EDefine and drive enterprise data engineering architecture, standards, and best practices across the organization.%3C/li%3E%3Cli%3EDesign and deliver scalable, high-performance data platforms supporting analytics, machine learning, and generative AI use cases.%3C/li%3E%3Cli%3EArchitect data lake, warehouse, and lakehouse solutions using Databricks, Delta Lake, and Unity Catalog.%3C/li%3E%3Cli%3EDesign and deliver data platform capabilities that support generative AI and agent-based workloads, including embedding pipelines, vector store integration, and knowledge base management.%3C/li%3E%3Cli%3EIdentify systemic gaps in data quality, reliability, performance, and cost, and drive solutions end-to-end.%3C/li%3E%3Cli%3EEstablish reusable frameworks, patterns, and playbooks for data pipeline development adopted across teams.%3C/li%3E%3Cli%3EDefine data partitioning, optimization, and caching strategies for high-volume and low-latency workloads.%3C/li%3E%3Cli%3ELead technical design reviews and architecture decision records (ADRs) for major data platform initiatives.%3Cbr%3E%26nbsp;%3C/li%3E%3C/ul%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3EAI/GenAI Data Infrastructure (20%)%3C/strong%3E%3C/p%3E%3Cul%3E%3Cli%3EDesign and implement data architectures that serve AI/ML model training, RAG pipelines, and agent-based systems.%3C/li%3E%3Cli%3EBuild and govern embedding pipelines, vector database ingestion workflows, and knowledge base refresh processes.%3C/li%3E%3Cli%3EDefine data quality, freshness, and governance standards for AI-consumed datasets.%3C/li%3E%3Cli%3EArchitect unstructured data processing pipelines (document parsing, chunking strategies, metadata enrichment) for GenAI consumption.%3C/li%3E%3Cli%3ECollaborate with LLMOps and AI Solutions engineers to define data contracts and integration patterns between data platform and AI systems.%3C/li%3E%3Cli%3EEvaluate and integrate emerging data technologies that support AI workloads (vector databases, graph databases, semantic search).%3Cbr%3E%3Cbr%3E%26nbsp;%3C/li%3E%3C/ul%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3ETechnical Leadership %26amp; Strategy (20%)%3C/strong%3E%3C/p%3E%3Cul%3E%3Cli%3EOperate in high-ambiguity environments by defining problem statements, success metrics, and technical approach.%3C/li%3E%3Cli%3EInfluence technology decisions and contribute to organizational data and platform strategy.%3C/li%3E%3Cli%3EMentor and coach data engineers across the team, establishing technical growth paths and skill development.%3C/li%3E%3Cli%3EDrive adoption of engineering best practices including code review standards, testing frameworks, and CI/CD maturity.%3C/li%3E%3Cli%3ERepresent data engineering in cross-functional planning with AI engineering, analytics, and business teams.%3C/li%3E%3Cli%3EEvaluate emerging technologies, frameworks, and engineering approaches for potential adoption.%3C/li%3E%3Cli%3EContribute to enterprise-wide data strategy, platform roadmap, and architecture governance discussions.%3Cbr%3E%3Cbr%3E%26nbsp;%3C/li%3E%3C/ul%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3EOperational Excellence %26amp; Governance (10%)%3C/strong%3E%3C/p%3E%3Cul%3E%3Cli%3EDefine and enforce data governance policies including classification, access control, lineage, and retention.%3C/li%3E%3Cli%3EEstablish monitoring, alerting, and SLA frameworks for critical data pipelines and data products.%3C/li%3E%3Cli%3EDrive incident response processes, root cause analysis, and preventive measures for data platform issues.%3C/li%3E%3Cli%3EImplement cost optimization strategies for cloud data infrastructure and compute resources.%3C/li%3E%3Cli%3E%3Cp%3EEnsure compliance with regulatory requirements and responsible data practices.%3C/p%3E%3Cp%3E%26nbsp;%3C/p%3E%3Cp%3E%26nbsp;%3C/p%3E%3C/li%3E%3C/ul%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3ECollaboration %26amp; Stakeholder Engagement (10%)%3C/strong%3E%3C/p%3E%3Cul%3E%3Cli%3EPartner with business stakeholders, product owners, and domain experts to translate business needs into data solutions.%3C/li%3E%3Cli%3EAlign with AI engineering teams (LLMOps, AI Solutions) to ensure seamless data-to-AI integration.%3C/li%3E%3Cli%3ECommunicate technical decisions, trade-offs, and roadmap to both technical and non-technical audiences.%3C/li%3E%3Cli%3E%3Cp%3EFacilitate knowledge transfer and documentation practices across the data engineering team.%3C/p%3E%3Cp%3E%26nbsp;%3C/p%3E%3Cp%3E%26nbsp;%3C/p%3E%3C/li%3E%3C/ul%3E%3Cp%3E%3Cbr%3E%3Cstrong%3EDay-to-Day Activities%3C/strong%3E%3C/p%3E%3Cp%3EA typical week in this role involves a blend of strategic architecture work, hands-on engineering, mentorship, and cross-functional collaboration:%3C/p%3E%3Cul%3E%3Cli%3EDesigning data models and pipeline architectures for new business requirements, drawing architecture diagrams and writing technical design documents.%3C/li%3E%3Cli%3EWriting and reviewing complex data transformation code in Databricks (Python, Spark, SQL) for high-volume and high-complexity use cases.%3C/li%3E%3Cli%3ELeading technical design sessions with the team to solve ambiguous data challenges and establish patterns for reuse.%3C/li%3E%3Cli%3EReviewing pull requests and providing architectural guidance and mentorship to team members.%3C/li%3E%3Cli%3EMeeting with AI engineering teams (LLMOps, AI Solutions) to align on data contracts, embedding pipeline requirements, and vector store integration.%3C/li%3E%3Cli%3EInvestigating and resolving complex production issues including performance bottlenecks, data quality degradations, and pipeline failures.%3C/li%3E%3Cli%3EEvaluating new tools and technologies (e.g., vector databases, streaming frameworks, governance tooling) through proof-of-concepts.%3C/li%3E%3Cli%3EParticipating in architecture review boards and contributing to enterprise data strategy discussions.%3C/li%3E%3Cli%3EDefining and tracking data platform KPIs (pipeline reliability, data freshness, query performance, cost efficiency).%3C/li%3E%3Cli%3EConducting 1:1 mentoring sessions with junior and mid-level data engineers on technical growth.%3C/li%3E%3Cli%3ECollaborating with data governance and security teams on access policies, data classification, and compliance requirements.%3C/li%3E%3Cli%3EWriting and maintaining engineering playbooks, architectural decision records, and onboarding documentation.%3Cbr%3E%26nbsp;%3C/li%3E%3C/ul%3E%3Cp%3E%26nbsp;%3C/p%3E%3Cul%3E%3Cli%3EProvide technical mentorship and guidance across the AI gineering organization.%3C/li%3E%3Cli%3ESupport knowledge sharing, cross-training, and engineering excellence initiatives.%3Cbr%3E%26nbsp;%3C/li%3E%3C/ul%3E%3Cp class=%22MsoNormal%22%3E%26nbsp;%3C/p%3E
%3Cp class=%22MsoNormal%22%3E%3Cstrong%3ETechnical Skills %26amp; Tools%3C/strong%3E%3C/p%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3EEducation%3C/strong%3E%3C/p%3E%3Cp class=%22MsoNormal%22%3EBachelor%27s degree in Computer Science, Computer Engineering, Data Science, Information Systems, or equivalent. Master%27s degree preferred.%3C/p%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3ERequired Knowledge, Skills %26amp; Abilities%3C/strong%3E%3C/p%3E%3Cul%3E%3Cli%3E4-6+ years of progressive data engineering experience with increasing scope and complexity.%3C/li%3E%3Cli%3EDeep expertise in Python, SQL, Scala, and distributed data systems (Apache Spark, Delta Lake).%3C/li%3E%3Cli%3EStrong experience with Azure Cloud, Databricks Lakehouse platform, Unity Catalog, and Databricks Workflows.%3C/li%3E%3Cli%3EExperience with Docker, Kubernetes, and CI/CD pipelines for data engineering workloads.%3C/li%3E%3Cli%3EAdvanced monitoring and logging (Azure Monitor, Log Analytics, Databricks observability).%3C/li%3E%3Cli%3EProven ability to design and deliver enterprise-scale data architectures (data lake, warehouse, lakehouse).%3C/li%3E%3Cli%3EExperience with data architectures supporting AI/ML workloads (e.g., vector databases, embedding pipelines, unstructured data processing).%3C/li%3E%3Cli%3EStrong data modeling skills (dimensional, data vault, lakehouse medallion patterns).%3C/li%3E%3Cli%3EExperience defining and enforcing data governance, quality, and security standards.%3C/li%3E%3Cli%3ETrack record of mentoring engineers and establishing engineering best practices.%3C/li%3E%3Cli%3EExcellent communication skills with ability to influence technical decisions across teams.%3Cbr%3E%3Cbr%3E%26nbsp;%3C/li%3E%3C/ul%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3EPreferred Knowledge, Skills %26amp; Abilities%3C/strong%3E%3C/p%3E%3Cul%3E%3Cli%3EExperience with Databricks Mosaic AI, Unity Catalog for AI governance, and Feature Store.%3C/li%3E%3Cli%3EFamiliarity with RAG architectures, vector search (e.g., Pinecone, Weaviate, Azure AI Search), and embedding models.%3C/li%3E%3Cli%3EExperience with streaming data platforms (Kafka, Event Hubs, Spark Structured Streaming).%3C/li%3E%3Cli%3EKnowledge of LangChain or similar frameworks (understanding data requirements, not application development).%3C/li%3E%3Cli%3EExperience with graph databases and knowledge graph architectures.%3C/li%3E%3Cli%3EInfrastructure-as-code experience (Terraform, ARM templates, Bicep).%3C/li%3E%3Cli%3EBasic experience with Power BI or similar tools for semantic-layer-based data discovery.%3C/li%3E%3Cli%3EFamiliarity with SAFe Agile or similar scaled agile frameworks.%3C/li%3E%3Cli%3EExperience operating in regulated environments with data compliance requirements.%3Cbr%3E%3Cbr%3E%3Cbr%3E%26nbsp;%3C/li%3E%3C/ul%3E%3Cp class=%22MsoNormal%22%3E%3Cstrong%3EAdditional Information%3C/strong%3E%3C/p%3E%3Cul%3E%3Cli%3EMust be able to work flexible hours/work schedule.%3C/li%3E%3Cli%3ETravel domestically and internationally as needed.%3C/li%3E%3Cli%3EWork holidays and weekends when required for production support or critical deliveries.%3C/li%3E%3Cli%3EEnjoys collaborative work and technical mentoring with peers and junior team members.%3C/li%3E%3Cli%3EA self-starter who thrives in ambiguous environments and drives clarity through technical leadership.%3C/li%3E%3Cli%3EThis role is part of MBUSA%27s Data Insights %26amp; AI organization and contributes to the company%27s data and AI strategy and operating model.%3Cbr%3E%26nbsp;%3C/li%3E%3C/ul%3E%3Cp style=%22font-family:Arial;margin-bottom:11px;%22%3E%26nbsp;%3C/p%3E%3Cp style=%22font-family:Arial;margin-bottom:11px;%22%3E%3Cspan style=%22font-family:Calibri,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22border:1.0pt none windowtext;line-height:107%;padding:0in;%22%3E%3Cstrong%3EEEO Statement%3C/strong%3E%3C/span%3E%3C/span%3E%3C/p%3E%3Cp style=%22font-family:Arial;%22%3E%3Cspan style=%22background-color:white;font-family:Calibri,sans-serif;font-size:10.0pt;%22%3E%3Cspan style=%22line-height:15.0pt;vertical-align:baseline;%22%3EMercedes-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.%3C/span%3E%3C/span%3E%3C/p%3E

Job Details
Group: Mercedes-Benz Group AG
Organization: Mercedes-Benz USA, LLC
Primary Location: United States of America-Georgia-Atlanta
Work Locations: One Mercedes-Benz Drive, Atlanta, 30328