Senior Data Engineer

About GraderaGradera defines a new category of enterprise transformation called Software-Orchestrated Services™ - where software orchestrates human expertise, digital workers, and enterprise systems to deliver governed outcomes at scale. As an AI Native Services firm, we help enterprises redesign how work gets done across operations, product, engineering, customer experience, data, and enterprise workflows to move beyond fragmented AI pilots and disconnected automation toward measurable business outcomes.OverviewWe are seeking a hands-on, collaborative Senior Data Engineer to drive the technical direction, architecture, and delivery of our data foundation for digital twin and AI-powered enterprise platforms. As Senior Data Engineer, you will be ensuring the delivery of robust, scalable, high-performance data pipelines that power real-time operational intelligence and simulation-ready data products. This role partners closely with data architects, simulation engineers, ML engineers, and platform teams.Our core data platform stack includes:Data Platform & LakehouseDatabricks as the single point of truth for all dataDatabricks SQL for analytical queriesUnity Catalog for metadata management and governanceTerradata for data warehouse and business <intelligence.Stream> & Event ProcessingApache Kafka for real-time event ingestion and streamingStructured Streaming for continuous data processingDelta Live Tables for declarative, quality-enforced pipelinesSpecialized Data StoresTimescaleDB for time-series operational dataTransformation & workflowsPython, Scala, and SQL for data transformation and orchestrationAI/ML workflows on Databricks modelsData Quality & GovernanceGreat Expectations and Delta Live Tables expectations for data validationUnity Catalog for metadata management and complianceWork with Time‑series databases is a plusKey ResponsibilitiesArchitect and build data foundations that serve digital twin platforms, AI/ML workloads, and operational analyticsEnsure delivery of high-quality, well-governed, and performant data products using Unity Catalog and Delta LakeDrive adoption of DataOps best practices, including CI/CD for data pipelines, automated testing, and monitoringChampion data hygiene, quality frameworks, and observability across the data estateOversee real-time data ingestion from diverse operational systems and IoT sourcesGuide the use of modern data engineering tools, architectural patterns, and emerging technologiesOwn the implementation and quality of data lineage, cataloging, and governance to enable trust and complianceCollaborate with simulation engineers and ML teams to deliver simulation-ready and feature-engineered datasetsEnsure engineering rigor, code quality, and documentation standards are met across the data stackFacilitate clear communication, knowledge sharing, and effective documentation within the teamDrive development efficiency and alignment with product team priorities through clear prioritization frameworks and delivery metrics.Preferred Qualifications5 to 7 years of hands-on data engineering experienceTrack record of architecting and delivering scalable, production-grade data platformsExperience with modern DataOps practices (CI/CD for data, automated testing, pipeline monitoring)Experience working in cross-functional, agile teams Highly DesirableExperience building data foundations for digital twin or simulation platformsFamiliarity with OpenUSD data pipelines or FMI/FMU data integrationExperience with physics-informed or operational ML feature engineeringTrack record of delivering data platforms with sub-second latency for real-time operational use casesExperience thriving in fast-paced, ambiguous environments and balancing rapid delivery with technical excellenceExposure to industrial domains such as Manufacturing, Logistics, or Transportation is a plus.