About The Role

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 skilled Data Engineers to join our Data & Digital Twin Foundation team. You will design, build, and maintain data pipelines that power digital twin platforms, real-time operational systems, and AI/ML workloads. Working closely with data architects, simulation engineers, and ML teams, you will transform raw operational data into high-quality, governed datasets that drive intelligent decision-making. Key ResponsibilitiesDesign, develop, and maintain scalable data pipelines using Databricks, PySpark, and Delta LakeBuild real-time and batch data ingestion pipelines from diverse operational systems using high-performance Kafka data pipelines.Implement data transformations that serve digital twin platforms and operational analyticsIntegrate Kafka event streams with Databricks for real-time operational state updatesImplement data quality checks using Delta Live Tables expectationsEnsure data governance compliance through Unity Catalog (lineage, access control, metadata)Optimize pipeline performance, reliability, and cost efficiencyWrite clean, well-documented, and testable code following engineering best practicesCollaborate with ML engineers to deliver feature-engineered datasetsParticipate in code reviews, knowledge sharing, and continuous improvement initiativesSupport production data systems through monitoring, troubleshooting, and incident <resolution.Build> business data warehouse solutions using Terradata for business intelligence. Our core data platform stack includes:Data Platform & LakehouseDatabricks as the single point of truth for all dataRealtime Data Pipelines implemented using Kafka for data ingestion.Databricks SQL for analytical queriesUnity Catalog for metadata management and governanceTerradata for data warehouse and business <intelligence.Stream> & Event ProcessingApache Kafka for real-time event ingestionStructured Streaming for continuous data processingDelta Live Tables for declarative, quality-enforced pipelinesData QualityDelta Live Tables expectations for data validationData profiling and anomaly detectionPreferred Qualifications7+ years of hands-on data engineering experienceTrack record of building and maintaining production-grade data pipelinesExperience with Delta Live Tables for declarative pipeline developmentExperience working in agile, cross-functional teamsFamiliarity with time-series data patterns and operational data modellingHighly DesirableExperience building data pipelines for digital twin or simulation platformsFamiliarity with operational state modeling for real-time systemsExposure to physics-informed or time-series ML feature engineeringExperience working with distributed, multidisciplinary teamsExposure to industrial domains such as Manufacturing, Logistics, or Transportation is a plus

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