Data Architect - AWS - Erie, PA Onsite - W2

Role: Data Architect - AWS

Primary Skill: Data lake, AWS, Athena, Glue, Iceberg, Snowflake, Terraform

Location: Erie PA Onsite - 5 Days a week

Key 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 solutions.

Collaborating 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 platform

Developing 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 maturity.

Lead strategy session for Data & Analytics maturity with a focus of fulfilling business requirements around performance, scalability, flexibility, and cost

Provide insights into modern Data & Analytic technologies and new use cases business intelligence and predictive analytics

Lead 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 driven.

Assess the Customers' knowledge of AWS platform and overall cloud readiness to support customers through a structured learning plan and ensure its delivery.

Desired Skill, Experience

Should have 14 years of experience with last 4 years in implementing Cloud native Data Solutions for variety of data consumption needs such as Modern Data warehouse, BI, Insights and Analytics

Should have experience in architecture and implementing End to End Modern Data Solutions using AWS and advance data processing frameworks like Databricks etc.

Strong knowledge of cloud native data platform architectures, data engineering, and data management

Good knowledge of popular database and data warehouse technologies from Snowflake and AWS

Demonstrated knowledge of data warehouse concepts. Strong understanding of Cloud native databases, columnar database architectures

Ability to work with Data Engineering teams, Data Management Team, BI and Analytics in a complex development IT environment.

Good appreciation and at least one implementation experience on processing substrates in Data Engineering - such as ETL Tools, Confluent Kafka, ELT techniques

Exposure 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 practice.

Preferable (Nice to have): Implementing analytic models using AWS SageMaker for production workloads.

Data Mesh and Data Products designing, and implementation knowledge will be an added advantage.