Delivery Consultant- Data, WWPS ProServe Data and Machine Learning

Delivery Consultant- Data, WWPS ProServe Data and Machine Learning jobs in United States

Amazon

• +1 more
• $131K/yr - $178K/yr

Responsibilities

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

Preferred

• Experience building data platforms with AWS services such as Glue, Lake Formation, Athena, Kinesis, and Lambda
• Experience with CI/CD automation (CDK or Terraform), physical data modeling (Dimensional, Data Vault), and data pipeline optimization
• Experience leading end-to-end data engineering projects including migrating on-premises data applications to cloud-native architectures
• Experience interfacing with customers at different organizational levels to translate requirements into scalable data architectures
• Knowledge of security and compliance standards (e.g., FedRAMP, NIST, HIPAA)

Benefits

• Sign-on payments
• Restricted stock units (RSUs)
• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• Paid time off
• Parental leave
• Glassdoor
• 3.7
• Amazon is a tech firm with a focus on e-commerce, cloud computing, digital streaming, and AI infrastructure.
• Seattle, Washington, USA
• https://amazon.com
• Public Company
• Total Funding
• $65.74B
• Key Investors
• Thrive Capital
• Kleiner Perkins
• 2026-09-09
• Post Ipo Debt· $5.76B
• 2026-08-14
• Post Ipo Equity· $215M
• 2026-07-09
• Post Ipo Debt· $24.92B
• Leadership Team
• Andrew Jassy
• President and CEO
• Werner Vogels
• VP & CTO
• Recent News
• Retail Dive

Qualifications

• Bachelor's degree in business administration, finance, economics, computer science, data science, engineering, or other related field
• 3+ years of database (eg. SQL, NoSQL, Hadoop, Spark, Kafka, Kinesis) experience
• Experience with SQL, Python, schema definition, and software engineering best practices including secure, testable, and maintainable code
• Understanding of distributed systems, data integration techniques (ETL vs. federation), database optimization (partitioning, indexing), and relational database performance tuning
• Current, active US Government Security Clearance of Top Secret or above
• Experience building data platforms with AWS services such as Glue, Lake Formation, Athena, Kinesis, and Lambda
• Experience with CI/CD automation (CDK or Terraform), physical data modeling (Dimensional, Data Vault), and data pipeline optimization
• Experience leading end-to-end data engineering projects including migrating on-premises data applications to cloud-native architectures
• Experience interfacing with customers at different organizational levels to translate requirements into scalable data architectures
• Knowledge of security and compliance standards (e.g., FedRAMP, NIST, HIPAA)

Required skills

• AWS Athena, AWS CDK, AWS Glue, AWS Lake Formation, AWS Lambda, CI/CD Automation, Cloud Data Platforms, Cloud-native Architectures, Customer Interaction, Data Architecture, Data Engineering, Data Integration Techniques, Data Lakes, Data Pipeline Optimization, Data Vault Modeling, Data Warehouses, Database Optimization, Dimensional Modeling, Distributed Systems, ETL, FedRAMP, HIPAA, Hadoop, Indexing, Kafka, Kinesis, NIST, NoSQL, Partitioning, Physical Data Modeling, Python, Relational Database Performance Tuning, SQL, Schema Definition, Security and Compliance Standards, Software Engineering Best Practices, Spark, Terraform

Experience

• 3+ years