{"id":3878883,"url":"https://alion.io/job/inclusion-cloud-big-data-engineer","title":"Big Data Engineer","company":{"id":3875981,"name":"Inclusion Cloud","domain":"inclusioncloud.com","url":"https://alion.io/company/inclusion-cloud","size_band":"201-500","is_staffing_agency":false,"employer_type":"staffing","is_intermediary":false,"listed_via":null,"ats_vendor":"Manatal","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"GCP","optional":false},{"name":"Hadoop","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Oracle","optional":true}],"status":"live","first_seen_at":"2026-11-06T17:32:12Z","employer_posted_date":"2026-11-06","last_verified_at":"2026-11-08T16:08:28Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"About the Role\nWe are seeking a Senior Big Data Engineer with strong experience in Business Intelligence, Machine Learning, and AI-driven solutions to join our data and analytics team. This role is ideal for a hands-on professional who can design, build, and optimize large-scale data platforms while enabling advanced analytics and AI use cases.\nThe candidate must be able to communicate fluently in English, as they will work closely with international stakeholders, data scientists, product teams, and business users.\nKey Responsibilities\nDesign, build, and maintain scalable Big Data architectures for analytics, BI, and AI use cases.\n\nDevelop and optimize batch and streaming data pipelines, including real-time ingestion using Kafka, to process large volumes of data from multiple sources.\n\nDesign and manage Kafka-based event-driven and streaming architectures.\n\nEnable Business Intelligence solutions, ensuring data availability, quality, and performance for dashboards and reports.\n\nCollaborate with Data Scientists and ML Engineers to prepare data for Machine Learning and AI models.\n\nSupport the deployment, monitoring, and optimization of ML and AI models in production environments.\n\nWork closely with business and analytics teams to translate business requirements into technical data solutions.\n\nEnsure data governance, security, and compliance across data platforms.\n\nOptimize data performance, cost, and reliability in cloud-based environments.\n\nDocument data models, pipelines, and architectural decisions.\n\nRequired Skills & Experience\n5+ years of experience in Big Data Engineering or similar data-focused roles.\n\nStrong hands-on experience with Apache Kafka, including:\nDesigning and implementing streaming pipelines\n\nWorking with topics, producers, consumers, and schemas\n\nSupporting real-time or near real-time data processing\n\nStrong experience with Big Data technologies such as Spark, Hadoop, Databricks, and related ecosystems.\n\nSolid background in Business Intelligence, including data modeling and support for reporting and dashboards.\n\nHands-on experience working with Machine Learning and AI use cases, including data preparation and model integration.\n\nProficiency in SQL and at least one programming language such as Python or Scala.\n\nExperience with cloud platforms (AWS, Azure, or GCP).\n\nStrong knowledge of data warehousing and data lake architectures.\n\nExperience working with structured and unstructured data.\n\nStrong problem-solving and analytical skills.\n\nFluent English (spoken and written) is mandatory.\n\nNice to Have\nExperience supporting AI/ML pipelines in production.\n\nKnowledge of MLOps concepts and tools.\n\nExperience with real-time or streaming analytics.\n\nFamiliarity with data governance and data quality frameworks.\n\nExperience working on Oracle-based projects (Oracle Database, Oracle Analytics, Oracle Cloud Infrastructure) is a strong plus.\n\nExperience working in international or distributed 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