Sr. Delivery Consultant- Data & Analytics, Wwps, Proserve Non Profits Organization (npo)

Amazon Amazon · Big Tech · Chicago, IL · Data Science

This role focuses on data engineering and architecture, helping public sector customers design and build data lakes, data warehouses, and scalable data platforms in the cloud. It involves translating business outcomes into data solutions, collaborating with stakeholders, and acting as a trusted advisor on data technologies.

What you'd actually do

  1. Helping clarify customer business outcomes during project discovery and translating them into data architecture and engineering solutions
  2. Designing and building data analytics applications that are secure, scalable, reliable, performant, and cost-effective
  3. Collaborating with stakeholders to gather requirements, assess current infrastructure, and propose effective data migration and modernization strategies
  4. Identifying, mitigating, and communicating risks related to solution and service constraints by making informed technical trade-offs
  5. Acting as a trusted advisor to customers on industry trends, emerging data technologies, and innovative solutions
  6. Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts

Skills

Required

  • Data Engineering
  • Data Architecture
  • Cloud Data Platforms
  • SQL
  • Python
  • Database experience (SQL, NoSQL, Hadoop, Spark, Kafka, Kinesis)
  • Cloud solution experience (AWS or equivalent)
  • System, network, and operating system experience
  • Customer facing experience
  • Project management experience
  • Schema definition
  • Software engineering best practices

Nice to have

  • AWS Professional level certification
  • Knowledge of AWS services (compute, storage, networking, security, databases, machine learning, serverless)
  • Knowledge of security and compliance standards (HIPAA, GDPR)
  • Performance optimization and cost management for cloud environments
  • CI/CD automation (CDK or Terraform)
  • Physical data modeling (Dimensional, Data Vault)
  • Data pipeline optimization
  • Migrating on-premises data applications to cloud-native architectures

What the JD emphasized

  • 7+ years of technical specialist, design and architecture experience
  • 5+ years of database (eg. SQL, NoSQL, Hadoop, Spark, Kafka, Kinesis) experience
  • 3+ years of cloud based solution (AWS or equivalent), system, network and operating system experience
  • 7+ years of external or internal customer facing, complex and large scale project management experience
  • 5+ years of cloud architecture and solution implementation experience
  • Experience with SQL, Python, schema definition, and software engineering best practices including secure, testable, and maintainable code