Pay rate range - $100/hr. to $105/hr.
Onsite
Must Have
Informatica workflow design and implementation required
AWS data engineering (Glue, Lambda, EventBridge Cradle, S3) highly preferred
Former Informatica exp, date bricks snowflake
Nice to Have
Apache Airflow
Someone who is fun and exciting with lots energy
Articulation
Job Description:
As a Data Engineer on the client team you will routinely solve complex data problems, unblocking critical projects that drive mission to be "the daily destination for style inspiration and discovery." Whether you are optimizing analytics that help marketing tune their strategies, building new pipelines to speed up delivery, partnering with our Science team to deliver AI solutions, or helping accounting drill down to track our business: your work will empower meaningful change for your customers. You will partner closely with stakeholders across the business and with the Data Engineering team to deliver new features, or pitch in to migrate legacy features to a modern AWS-based platform. You will be an active partner in the broader data engineering community, taking part in learning series and operational reviews with industry-leading engineers.
The data engineering team frequently collaborates with teams across the business, providing opportunities to learn about the fashion industry and e-commerce (and employee discounts).
Key job responsibilities
You will own projects that build new data pipelines, modernize existing ones onto our AWS-based platform, or refine pipelines to deliver more value for our customers.
You will partner with colleagues across to understand their business domains and build solutions that meet their needs, including working with our Science team to bring AI solutions to production.
You will also be an active participant on the data team, driving improvements to the team's operational health and reducing errors for customers. And you will take part in engineering culture, learning from and teaching alongside the best, while making the most of AI-powered tools to work more effectively.
Some of your tasks will include:
• Architecting, designing, and implementing next-generation data pipelines and BI solutions built on AWS
• Building and optimizing ETL processes to improve data quality, reliability, and freshness
• Leveraging AI-powered developer and data tools to boost your own productivity and code quality
• Partnering with business stakeholders to translate their needs into scalable data solutions
• Collaborating with the Science team to build data foundations for AI solutions and bring them into production
• Improving the team's operational excellence through monitoring, automation, and error reduction