Role Description We are seeking an Engineering Subject Matter Expert to help develop next-generation AI systems by applying real-world engineering expertise to evaluate, create, and improve technical content. In this role, you will review engineering documentation, assess technical accuracy, and contribute practical engineering knowledge that enhances AI reasoning and performance. No prior AI experience is required—your engineering expertise is what matters most. Key Responsibilities - Technical Review & Analysis - Review and analyze engineering documentation, including technical reports, design documents, specifications, and project analyses. - Evaluate engineering submissions for technical accuracy, completeness, clarity, and adherence to industry best practices. - Provide detailed technical feedback, clarifications, and expert recommendations on complex engineering scenarios. - Content Development - Develop real-world engineering examples, case studies, and problem sets across various engineering disciplines. - Create structured technical explanations to help improve AI understanding of practical engineering concepts. - Ensure all technical content is accurate, well-organized, and aligned with engineering principles. - AI Model Evaluation - Assess AI-generated engineering responses for correctness, logical reasoning, and technical rigor. - Identify errors, inconsistencies, or gaps in engineering outputs and provide actionable feedback to improve model performance. - Contribute to the development of high-quality engineering datasets for AI training and evaluation. - Collaboration & Process Improvement - Work closely with project teams to ensure deliverables align with project milestones and quality standards. - Share industry best practices and technical insights to enhance project methodologies. - Collaborate effectively in a remote environment while maintaining high-quality documentation and deliverables. Qualifications - Bachelor's, Master's, or PhD in Mechanical, Civil, Electrical, Chemical, Industrial, Aerospace, Electronics, Manufacturing, or any other Engineering discipline. - Experience preparing technical reports, engineering documentation, design specifications, or project analyses. - Strong analytical and problem-solving skills with attention to technical detail. - Excellent written and verbal communication skills with the ability to explain complex engineering concepts clearly. - Ability to work independently and manage deliverables in a remote work environment. Preferred Qualifications - Experience working on multidisciplinary or cross-functional engineering projects. - Ability to communicate technical concepts effectively to both technical and non-technical audiences. - Familiarity with engineering standards, regulatory compliance, quality assurance, or industry best practices. - Experience reviewing engineering documentation or providing technical guidance. - Passion for innovation, technology, and engineering education. Must-Have Skills - Engineering Documentation - Technical Analysis - Technical Report Writing - Problem Solving - Engineering Design Review Good-to-Have Skills - Quality Assurance - Regulatory Compliance - Technical Documentation - Cross-functional Collaboration - Engineering Standards - Project Analysis - Design Documentation - Research & Technical Writing

• Design the ETL, transformation, and modeling patterns the team builds on • Build and maintain data ingestion pipelines that move data reliably from source into the warehouse • Build and maintain transformation models — client-specific and shared • Own data quality monitoring end-to-end: define what we monitor and to what SLA — not just tune thresholds — and decide where to spend the coverage budget • Understand the full data flow from raw event ingestion through final reporting tables • Own the complex, ambiguous requests and build the self-serve tooling that keeps the routine queue off engineering's plate

• You explore, implement the latest AWS and big data technologies to uncover hidden opportunities, enable new capabilities, and build integrations for the SIXT Data Shop • You design, build, and operate the core infrastructure underpinning the Data Platform — including Kubernetes workloads, AWS services, and reusable Terraform modules — with a focus on reliability, scalability, and developer experience • You partner with Data Engineers, BI Analysts, and Data Scientists to architect optimal solutions for diverse analytical use cases, including dashboarding, ad hoc analytics, data-as-a-product, and machine learning • You contribute to the Data Platform vision and roadmap through your expertise and intellectual curiosity, setting technical direction and engineering standards that the wider team builds on • You demonstrate the highest standards of integrity and data protection when handling sensitive customer data

• Legacy Data Platform Support • Maintain and enhance SSIS packages for data extraction, transformation, and loading • Support SQL Server data warehouse (staging, ODS, reporting layers) • Troubleshoot data issues, job failures, and performance bottlenecks • Optimize SQL queries, stored procedures, and indexing strategies • Ensure reliability of scheduled jobs via SQL Server Agent • Cloud Data Engineering (Azure + Databricks) • Design and develop data pipelines using Azure Data Factory (ADF) • Ingest and organize data into Azure Data Lake (Bronze/Silver/Gold layers) • Build scalable data transformations using Databricks (Spark SQL, PySpark) • Create curated, analytics-ready datasets for Power BI • Implement Delta Lake and support data governance (e.g., Unity Catalog) • Analyze and document existing SSIS/SQL pipelines • Translate legacy ETL processes into modern ELT patterns • Support phased migration strategy (coexistence of legacy and modern platforms) • Reduce technical debt and improve pipeline maintainability • Establish standards for data modeling, naming, and architecture • Design dimensional models (fact and dimension tables) aligned to business processes • Integrate and standardize data across multiple ERP systems • Translate business requirements into scalable data solutions • Partner with stakeholders to identify high-impact use cases for data and analytics • Deliver datasets that enable reporting, forecasting, and operational insights • Implement data validation, reconciliation, and monitoring processes • Ensure data accuracy and consistency across systems during migration • Define and enforce data quality standards and controls • Support data lineage, documentation, and transparency initiatives • Work closely with business stakeholders, analysts, and BI developers • Support Power BI semantic models and reporting solutions • Communicate technical solutions in business terms • Act as a bridge between IT/data teams and business functions