Data Solution Architect

Data Solution Architect

Responsibilities

• Design data analytics solutions by utilizing big data technology stacks
• Create and present solution architecture documents with comprehensive technical details
• Collaborate with business stakeholders to identify solution requirements and key case studies/scenarios for future implementations
• Lead solution implementation from project inception through deployment and "go-live" phases
• Conduct solution architecture reviews, audits, and ROI calculations, presenting findings and recommendations
• Engage in pre-sale activities by communicating directly with customers, processing RFPs, and developing tailored implementation proposals
• Lead presentations of proposed solution architectures to customer representatives and participate in technical discussions
• Stay current with industry trends and best practices to strengthen solution offerings
• Develop and follow a personal education plan within the relevant technology stack and solution architecture domain
• Support EPAM's business growth in the big data ecosystem by building strong client engagements
  

Requirements

• Strong hands-on experience in big data development with a solid design/development background in Java, Scala, or Python
• Experience delivering data analytics projects with clearly defined architecture guidelines
• Expertise in big data solutions across cloud platforms such as Microsoft Azure, Amazon Web Services, or Google Cloud
• Production project experience with at least one big data technology for use cases such as batch processing (e.g., Hadoop, Spark, Hive)
• Familiarity with NoSQL database systems including Cassandra, HBase, or Kudu
• Knowledge of Agile development methodologies, particularly Scrum
• Proficiency in direct customer communications and leading pre-sales business consulting engagements in enterprise environments
• Background in working within consulting firms combined with pre-sales experience is highly advantageous
  

Nice to have

• Skills in implementing data solutions on Databricks with deep proficiency in its ecosystem
• Familiarity with building modern data pipelines using Azure Synapse Analytics or Data Factory
• Understanding of advanced Spark optimization techniques for large-scale data processing
• Background in architecting complex data ecosystems with CI/CD pipelines across hybrid environments
• Capability to leverage cloud-native data services for machine learning or AI-powered analytics