FULL TIME: AWS Data Engineer - Maybelline - Hybrid/NYC-No H1-Need Locals

Requirement Notes (Candidate Job description below) : We need a mid-senior Data Engineer with experience building AWS Data Pipelines with (5 to 7+ years) designing and supporting data integrations and pipeline orchestration on AWS (Lambda, Step Functions, Fargate, Glue, etc). Snowflake experience required, 5 plus years. 3 plus years with SQL and Python. Retail industry exposure a plus. Experience with an integration platform like Oracle Integration Cloud a plus. Reporting tool experience such as Sigma a strong plus. Salesforce ecosystem exposure preferred (SFCC, SFSC, SFMC). Strong written and verbal communication skills. **** CANDIDATES CAN BE MIDLEVEL WITH 5+ YEARS AND HAVE GOOD AWS DATA PIPELINE EXPERIENCE – SNOWFLAKE IS A BIG PLUS BUT PLEASE STILL SEND CANDIDATES IF THEY DO NOT HAVE SNOWFLAKE – CERTIFICATIONS PREFERRED.

****CANDIDATES MUST HAVE GOOD TENURE AND/OR LONG PROJECTS. CANDIDATES WITH RECENT LOCAL PROJECTS HIGHLY PREFERRED. – NO RELOCATION

Job Description:

The Data Management and Engineering group builds modern data and analytics platforms for the business. We are hiring a Data Engineer to design and build integration solutions supporting a broader modernization push. The team is newly formed and growing fast, so this is a ground floor opportunity with an organization that has expanded steadily over the last three years.

What You''ll Build

·                  Translate business requirements into practical data solutions

• Serverless pipelines on AWS to move and transform data at scale
• Event driven architecture for decoupled, reliable data movement
• Real time system to database integrations using standardized frameworks
• Self service analytics tools giving business users access across multiple source systems
• CI/CD pipelines using Terraform and GitHub Actions across environments

Core Responsibilities
Pipeline work: build production grade pipelines on AWS serverless tools with solid error handling, retry logic, and observability. Implement data warehousing for historical tracking and compliance. Build incremental processing with change data capture and idempotent design. Create multi stage orchestration with parallel execution. Write and run test scripts before production release.

Integration work: connect enterprise systems (ERP, CRM, ecommerce, third party APIs) to each other and to the cloud data warehouse. Build event driven flows using AWS messaging and streaming tools. Design RESTful APIs with proper authentication for real time access. Build integrations spanning retail, supply chain, and finance systems.

Infrastructure and DevOps: manage cloud resources as code using Terraform. Build multi environment deployment pipelines with automated testing. Set up monitoring and alerting for pipeline health, data quality, and SLA tracking. Optimize cloud costs through serverless design and right sizing. Define security guardrails for data integrations.

Qualifications
5 to 7 years designing and supporting data integrations and pipeline orchestration on AWS (Lambda, Step Functions, Fargate, Glue, etc). Snowflake experience required, 5 plus years. 3 plus years with SQL and Python. Retail industry exposure a plus. Experience with an integration platform like Oracle Integration Cloud a plus. Reporting tool experience such as Sigma a strong plus. Salesforce ecosystem exposure preferred (SFCC, SFSC, SFMC). Strong written and verbal communication skills.

Education
Master''s in computer science, or bachelor''s with equivalent experience. Snowflake or Salesforce certifications a plus

AWS shop

Lambda

Data team. They do date integration. Lots of APIs. Moving data to other locations. 

Database is SnowFlake

DMS- data migration services 

Retail knowledge is helpful but not necessary