{"id":2494777,"url":"https://alion.io/job/gradera-data-engineer","title":"Data Engineer","company":{"id":4377760,"name":"Gradera","domain":"gradera.ai","url":"https://alion.io/company/gradera","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":42000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":55},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"Apache Kafka","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Digital Twin","optional":false},{"name":"pySpark","optional":false},{"name":"SQL","optional":false},{"name":"Agile","optional":true},{"name":"Python","optional":true},{"name":"Spark","optional":true},{"name":"Time Series Forecasting","optional":true}],"status":"live","first_seen_at":"2026-09-09T12:16:09Z","employer_posted_date":"2026-09-09","last_verified_at":"2026-10-14T16:47:27Z","board_verified":true,"closed_at":null,"days_open":35,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":35},"description":"About Gradera\nGradera 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\nOverview\nWe 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.\nKey Responsibilities\nDesign, develop, and maintain scalable data pipelines using Databricks, PySpark, and Delta Lake\n\nBuild real-time and batch data ingestion pipelines from diverse operational systems using high-performance Kafka data pipelines.\n\nImplement data transformations that serve digital twin platforms and operational analytics\n\nIntegrate Kafka event streams with Databricks for real-time operational state updates\n\nImplement data quality checks using Delta Live Tables expectations\n\nEnsure data governance compliance through Unity Catalog (lineage, access control, metadata)\n\nOptimize pipeline performance, reliability, and cost efficiency\n\nWrite clean, well-documented, and testable code following engineering best practices\n\nCollaborate with ML engineers to deliver feature-engineered datasets\n\nParticipate in code reviews, knowledge sharing, and continuous improvement initiatives\n\nSupport production data systems through monitoring, troubleshooting, and incident resolution.\n\nBuild business data warehouse solutions using Terradata for business intelligence.\nOur core data platform stack includes:\nData Platform & Lakehouse\nDatabricks as the single point of truth for all data\n\nRealtime Data Pipelines implemented using Kafka for data ingestion.\n\nDatabricks SQL for analytical queries\n\nUnity Catalog for metadata management and governance\n\nTerradata for data warehouse and business intelligence.\n\nStream & Event Processing\nApache Kafka for real-time event ingestion\n\nStructured Streaming for continuous data processing\n\nDelta Live Tables for declarative, quality-enforced pipelines\n\nData Quality\nDelta Live Tables expectations for data validation\n\nData profiling and anomaly detection\n\nPreferred Qualifications\n7+ years of hands-on data engineering experience\n\nTrack record of building and maintaining production-grade data pipelines\n\nExperience with Delta Live Tables for declarative pipeline development\n\nExperience working in agile, cross-functional teams\n\nFamiliarity with time-series data patterns and operational data modelling\n\nHighly Desirable\nExperience building data pipelines for digital twin or simulation platforms\n\nFamiliarity with operational state modeling for real-time systems\n\nExposure to physics-informed or time-series ML feature engineering\n\nExperience working with distributed, multidisciplinary teams\n\nExposure to industrial domains such as Manufacturing, Logistics, or Transportation is a 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