Job Title

Role : Technical ArchitectLocation: RemoteJob Description: Looking for skilled Solution Architect with deep expertise with expertise on Azure AI or BA Insights or Elastic Search and having good expertise on various database technologies (Network, Hierarchical, Relational, NoSQL), Big data ecosystems (Hadoop, Spark, Kafka, etc.), and cloud platforms (AWS, Azure, GCP). The candidate should have hands-on working experience using Oracle, IBM tool stacks, and middleware/container technologies in designing, implementing, and optimizing complex enterprise solutions. This role will involve in designing, architecting, overseeing implementation of complex, scalable, secure & high-performance solutions and optimizing large-scale data search and retrieval systems across distributed environments. Experience Requirements: years of experience of IT Experience. Minimum of 3 Years as Solution Architect or similar role, designing complex enterprise-level solutions involving Elastic Search Capabilities. Qualifications: Bachelors or masters degree in computer science, Engineering, or a related field. Primary Skill: Azure AI or Elastic Search or BA Insights Skill Requirements: Sound experience in solution architecture, database management, and enterprise IT solutions. Proven hands-on experience architecting solutions involving Azure AI & Search Technologies. Expertise in database technologies: Elastic Search. Good experience in architecting solutions across multiple cloud platforms (Preferably Azure). Expertise in database technologies: Oracle, SQL Server, MySQL, PostgreSQL, MongoDB, Cassandra, DynamoDB, IBM DB2, IMS. Proficiency on big data solutions using the Hadoop ecosystem (HDFS, Hive, HBase, Oozie, Pig, MapReduce, Spark, Scala, Kafka, Elasticsearch, Presto). Hands-on experience with data warehousing, ETL/ELT pipelines, and distributed computing. Experience in middleware and containerization: IBM WebSphere, IBM MQ, Oracle SOA, Docker, Kubernetes. Strong programming and scripting skills: Python, Java, SQL, Shell scripting. Deep understanding of networking, security, and compliance standards. Excellent analytical, problem-solving, critical-thinking and communication skills. Preferred Qualifications: Cloud certifications (AWS Certified Solutions Architect, Azure Solutions Architect, Google Professional Cloud Architect). Big Data certifications (Cloudera, Hortonworks, Databricks, etc.). Key Responsibilities: Design end-to-end technical solutions for complex business problems, integrating various technologies across databases, Big Data platforms, cloud services, and middleware. Develop and document architectural blueprints, technical specifications, data flow diagrams, and integration patterns. Define strategies for data ingestion, processing, storage, and analytics in large-scale distributed environments. Work with Elastic Search, and other distributed query engines for real-time analytics. Evaluate and recommend appropriate technologies from the available stack, based on requirements, performance, scalability, and cost-effectiveness. Design real-time data streaming pipelines using Apache Kafka, Spark Streaming. Architect big data solutions using the Hadoop ecosystem (HDFS, Hive, HBase, Oozie, Pig, MapReduce, Spark, Scala, Kafka, Elasticsearch, Presto). Provide best practices and governance policies for data security, integrity, and compliance. Optimize ETL/ELT pipelines for high-volume data processing. Collaborate with DevOps, Data Engineering, and Application Development teams to ensure seamless implementation of solutions. Guide technical teams in best practices for system performance, scalability, and high availability. Drive proof-of-concepts (PoCs) and assess emerging technologies for enterprise adoption. Develop and document architectural blueprints, technical specifications, data flow diagrams, and integration patterns. Develop and implement cloud-native architectures in preferably on Azure. Utilize Kubernetes, Docker, and other containerization technologies for microservices deployment. Integrate middleware solutions such as IBM WebSphere, IBM MQ, Oracle SOA Suite, Kafka to support enterprise data workflows.