Data Engineer

David Yurman•New York, NY

12d•$140,000 - $150,000•Hybrid

About The Position

The Data Engineer will join David Yurman’s Data Management & Engineering team, which designs and implements data and analytics solutions. This hybrid position in New York focuses on designing and building data integration solutions that support the company’s modernization efforts. The team is growing, offering an opportunity to join while it is in a formation state. The role involves developing production-grade data pipelines and integrations using AWS serverless and event-driven technologies, connecting enterprise systems and data platforms, and building self-service analytics capabilities. The engineer will also manage cloud infrastructure and deployments as code, establish monitoring and security guardrails, and improve pipeline reliability, data quality, and cloud cost efficiency.

Requirements

Minimum 5–7 years of experience designing, building, and supporting data integrations and pipeline orchestrations using AWS technologies such as AWS Lambda, Step Functions, Fargate, and Glue.
At least 5 years of experience with Snowflake.
At least 3 years of experience with programming languages such as SQL and Python.
Strong written and verbal communication skills.
A master’s degree in computer science, or a bachelor’s degree with equivalent work experience.

Nice To Haves

Familiarity with retail as a business.
Familiarity with Oracle Integration Cloud (OIC) or another integration platform.
Familiarity with reporting tools such as Sigma.
Familiarity with the Salesforce ecosystem, including SFCC, SFSC, and SFMC.
Snowflake or Salesforce certifications.

Responsibilities

Understand business needs and develop multiple solutions to meet them.
Design and build production-grade data pipelines using AWS serverless technologies, including error handling, retry logic, and observability.
Implement data warehousing patterns for historical tracking and compliance requirements.
Build incremental data processing workflows using change data capture (CDC) and idempotent designs.
Create multi-stage orchestration workflows with parallel execution capabilities.
Develop test scripts and test code before promoting it to production.
Connect enterprise systems, including ERP, CRM, e-commerce platforms, and third-party APIs, with each other and to a cloud data warehouse.
Build event-driven data flows using AWS messaging and streaming services.
Design RESTful APIs for real-time data access with appropriate authentication and authorization.
Develop integrations across retail, supply chain, and financial systems.
Write infrastructure as code using Terraform to manage 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.