{"id":1254046,"url":"https://alion.io/job/optimum-infosystem-enterprise-data-analytics-architect","title":"Enterprise Data & Analytics Architect","company":{"id":3800114,"name":"Optimum Solutions","domain":"theoptimum.net","url":"https://alion.io/company/optimum-infosystem","size_band":"1001-5000","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data 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Modeling","optional":false},{"name":"Embeddings","optional":false},{"name":"Flink","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"GraphDB","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"OpenShift","optional":false},{"name":"RAG","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"Terraform","optional":false},{"name":"Trino","optional":false}],"status":"closed","first_seen_at":"2026-09-19T00:00:00Z","employer_posted_date":null,"last_verified_at":"2026-10-03T20:00:59Z","board_verified":false,"closed_at":"2026-10-03T20:00:59Z","days_open":14,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":14},"description":"Key Responsibilities\nOwn the end-to-end Data & Analytics architecture and technical vision for the enterprise. \nDefine and drive the Data & Analytics strategy, roadmap, architecture principles, standards, and reference architectures. \nDesign and architect enterprise-scale Data Lakehouse and Data Platform solutions. \nLead architecture across Databricks, Snowflake, Cloudera, Azure, AWS, and GCP environments. \nDefine architecture patterns for Delta Lake, Apache Iceberg, Hudi, Object Storage, Data Federation, and distributed data processing. \nDevelop target-state architecture for enterprise data platforms, analytics platforms, Data Lakehouse, data warehouses, data products, and AI platforms. \nDefine scalable and reusable architecture patterns supporting business intelligence, reporting, advanced analytics, AI/ML, and GenAI. \nAssess existing data and analytics capabilities and identify opportunities for modernization, optimization, simplification, and technology transformation. \nEnsure Data & Analytics architecture aligns with enterprise technology, security, regulatory, risk, and governance requirements. \nArchitect solutions using Trino, Denodo, Dremio, Hive, Impala, and other distributed data technologies. \nDefine and establish an enterprise data product strategy. \nDesign reusable, discoverable, governed, and trusted data products for business and analytical consumption. \nSupport development of data marketplaces and self-service data platforms. \nEnable data products to support BI, reporting, analytics, AI/ML, and operational use cases. \nDefine architecture for Business Intelligence, reporting, dashboards, self-service analytics, and enterprise reporting platforms. \nPartner with business and analytics teams to understand KPIs, metrics, analytical requirements, and reporting needs. \nSupport development of descriptive, diagnostic, predictive, and advanced analytics capabilities. \nDefine scalable analytical data models and semantic layers for enterprise consumption. \nEnable trusted and consistent enterprise KPIs, metrics, and analytical insights. \nPromote self-service analytics while maintaining appropriate governance, security, and data quality. \nArchitect solutions for AI/ML, Generative AI, RAG, Vector Databases, Graph Databases, embeddings, and agentic AI workloads. \nDesign event-driven and streaming data architectures using Kafka, Flink, Spark Streaming, APIs, and messaging platforms. \nDefine modern engineering practices for Data & Analytics platforms using Terraform, Kubernetes/OpenShift, Git, Jenkins, CI/CD, and DevOps tools. \nPartner with business leaders, product owners, data analysts, data scientists, engineering teams, technology architects, and vendors. \nTranslate business requirements into practical and scalable Data & Analytics architecture. \nReview and approve solution designs, technical specifications, architecture decisions, and implementation approaches. \nProvide technical leadership to distributed engineering and delivery teams. \nEnsure projects follow enterprise architecture, security, governance, and engineering standards. \nDrive technical discussions, architecture reviews, design workshops, and technology evaluations. \nRequired Experience & Qualifications\n10–15 years of experience in Data & Analytics, Data Architecture, Data Engineering, Analytics Architecture, or related disciplines. \nStrong experience designing and implementing enterprise-scale Data & Analytics platforms. \nProven experience defining Data & Analytics strategy, architecture, roadmaps, and target-state architecture. \nStrong hands-on experience with Data Lakehouse, Data Warehouse, Data Platform, BI, and Advanced Analytics environments. \nExperience working in FSI/BFSI, banking, financial services, insurance, or other highly regulated environments is preferred. \nStrong expertise in one or more of Databricks, Snowflake, Cloudera, Azure, AWS, and GCP. \nStrong knowledge of Delta Lake, Apache Iceberg, Hudi, Object Storage, Data Federation, and distributed data platforms. \nExperience with Trino, Denodo, Dremio, Hive, Impala, or similar data technologies. \nStrong understanding of data modeling, data warehousing, dimensional modeling, semantic layers, metadata, lineage, and data governance. \nExperience designing data products, data marketplaces, analytical platforms, and self-service analytics. \nStrong understanding of BI, reporting, KPI management, analytical workloads, and advanced analytics. \nExperience with Kafka, Flink, Spark, Spark Streaming, APIs, real-time data, and event-driven architectures. \nStrong knowledge of RAG, Vector DB, Graph DB, embeddings, AI/ML, Generative AI, and agentic AI workloads. \nExperience with Terraform, Kubernetes/OpenShift, Git, Jenkins, CI/CD, and DevOps practices. \nStrong understanding of data security, privacy, access control, governance, data quality, and regulatory requirements. \nExperience with performance engineering, scalability, high availability, resiliency, and cloud cost optimization. \nSkills\nCloudera, Analytics Support, Distributed Platforms, Architectural Patterns, AWS, Data Warehouse Architectures, Data Solutions, Scientific Expertise, Business Intelligence architecture, Databricks, Data Governance, Data Architecture, Banking, Strategic Data Analysis, Regulated Financial Services, Data Strategy","description_format":"text","description_chars":5309,"description_truncated":false,"requirements":{"experience_years_min":10,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","IT Resellers & 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