Data Architect

Role: Data Architect (Modern Data Platform )Location: Erie, PALong TermKey Responsibilities:Our customers are looking for differentiating their businesses by leveraging Data as a strategic asset. You goal would be to engage customers in envisioning and building creative modern data solution such as cloud native Data platform implementation, BI and Analytics solutionsCollaborating with customer stakeholders, IT leadership, Architecture leadership to develop modern data solution and architecture, especially for cloud native Data platforms solution architecture using AWS cloud platformDeveloping technology roadmaps and best practice with precise steps of how to get there including architecture design, data modelling, and implementation of Modern Data platform and analytics use cases across the analytics maturityLead strategy session for Data & Analytics maturity with a focus of fulfilling business requirements around performance, scalability, flexibility, and costProvide insights into modern Data & Analytic technologies and new use cases business intelligence and predictive analyticsLead design, prototyping and delivery of software solutions within the cloud data eco-system to help develop new capabilities for customer business (P&C Insurance)Lead modern data solution conversations as technology expert to help customer see modern data solutions as enable for organization to be data drivenDesired Skill, Experience, Qualifications, Certifications etc.Should have 10+ years of experience with last 2 years in implementing Cloud native Data Solutions for variety of data consumption needs such as Modern Data warehouse, BI, Insights and AnalyticsShould have experience in architecture and implementing End to End Modern Data Solutions using AWS, Redshift, S3 and NoSQL databasesStrong knowledge of cloud native data platform architectures, data engineering and data managementGood knowledge of popular database and data warehouse technologies from Microsoft, Amazon, Redshift, Snowflake Microsoft Azure SQL Data WarehouseDemonstrated knowledge of data warehouse concepts. Strong understanding of Cloud native databases, columnar database architecturesAbility to work with Data Engineering teams, Data Management Team, BI and Analytics in a complex development IT environmentGood appreciation and at least one implementation experience on processing substrates in Data Engineering - such as AWS Glue, ETL Tools, Kafka, ELT techniquesExposure to varying databases - NoSQL (at very minimum Key value stores and/or Document stores), Appliances. Be able to cite implementation experiences constraints and performance challenges in practiceExposure to Streaming/Event based architecture - Unbounded, Bounded streams, maintaining states, constraints. Use of supporting technology blocks - low latency stores, messaging etc.Broad understanding of data consumption patterns such as spectrum of Analytics maturity, Data Warehousing, BI & Modern InsightsPreferable (Nice to have): Implementing analytic models using AWS SageMaker for production workloads