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# Data Engineer

- **Company:** David Yurman
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Salary:** $140,000.0 - $150,000.0
- **Contract:** Permanent contract
- **Skills:** Sql Data Warehouse, Application Programming Interfaces (APIs), Amazon Web Services, Business Analytics Applications, Automation of Tests, Databases, Data Integration, Data Retrieval, Data Warehousing, Github, Python (Programming Language), Salesforce.Com, SQL Databases, Data Streaming, Systems Integration, Delivery Pipeline, Snowflake, Test Scripts, AWS Lambda, Change Data Capture, Event Driven Architecture, Build Management, Information Technology, AWS Fargate, Enterprise Integration, Real Time Data, Data Management, Tools for Reporting, Restful APIs, Terraform, Oracle Integration, Data Pipelines, Serverless Computing, Programming Languages
- **Published:** October 12, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=ac228170b0e1f880

## About the Role

* Minimum 5-7 years of experience in designing, building, and supporting data integrations and pipeline orchestrations using AWS technologies such as AWS Lambda, Step Function, Fargate, Glue etc.
 * 5+ years' experience with Snowflake a must have
 * 3+ years' experience with programming languages - SQL, Python
 * Familiarity with retail as a business a nice to have
 * Familiarity with Oracle Integration Cloud (OIC) or other integration platform a plus.
 * Familiarity with reporting tools such as Sigma a huge plus.
 * Familiarity with Salesforce ecosystem preferred (SFCC, SFSC, SFMC)
 * Strong written and verbal communication skills

Education

 * Master's degree in computer science or bachelor's degree with equivalent work experience
 * Snowflake / salesforce certifications desirable

## Description

The Data Management & Engineering (DME) team at David Yurman (DY) is responsible to design & implement state of the art data & analytics solutions. We are looking for a dynamic Data Engineer to design and build data integration solutions to support DY's modernization efforts. This is a hybrid position with location in New York.

The DME team is in a formation state, and this is an exciting time to join and grow with an organization which is rapidly growing for the past 3 years.

What You'll Build

 * Understand business needs and develop multiple solutions to meet the needs
 * Serverless data pipelines using AWS Services to move and transform data at scale
 * Event-driven architectures for decoupled, reliable data flows
 * Real-time integrations between systems and databases through standardized enterprise integrations frameworks
 * Self-service analytics solutions that empower business users to access data across multiple
 * source systems
 * CI/CD pipelines using Terraform and GitHub Actions to deploy infrastructure across multiple
 * environments

Responsibilities

Pipeline Engineering:

 * Design and build production-grade data pipelines using AWS serverless technologies with proper error handling, retry logic, and observability
 * Implement data warehousing patterns for historical tracking and compliance requirements
 * Build incremental data processing workflows with change data capture (CDC) and idempotent
 * designs
 * Create multi-stage orchestration workflows with parallel execution capabilities
 * Develop appropriate test scripts and test the code before promoting to production.

Integration Development:

 * Connect multiple enterprise systems (ERP, CRM, e-commerce platforms, 3rd-party APIs) with
 * each other and to cloud data warehouse
 * Build event-driven data flows using AWS messaging and streaming services
 * Design RESTful APIs for real-time data access with proper authentication and authorization
 * Develop integrations across retail, supply chain, and financial systems

Infrastructure & DevOps:

 * Write Infrastructure as Code using Terraform to manage all cloud resources
 * Build multi-environment deployment pipelines with automated testing and validation
 * Implement monitoring and alerting for pipeline health, data quality, and SLA compliance
 * Optimize cloud costs through serverless architecture patterns and right-sizing
 * Define security guardrails within data integrations