We are looking for a passionate Data Engineer who would like to work with a top-notch technology stack in a friendly and cozy atmosphere for one of the greatest retail companies in the USA.

Why is this company one of the greatest? Founded in 1901, it prospered through two world wars, the Spanish flu, the Great Depression, the 2020 pandemic, and still produces the highest quality products and services for their customers.

The client’s company is based in Seattle with a technology orientation rooted in Silicon Valley. You will work with the cleverest minds, who are eager to build superb services to match business requirements and win market share.

And then there's Zoolatech! Just imagine a workplace and a team environment that you never want to leave once you have found it. Sound enticing? Apply to our position today and we can get you there.

Speaking about the core of the Client company’s analytics, Data Technology is pivotal to the Client’s customer experience. As a Data Engineer, you will own the design and build the next generation of Data & Analytical Services and deliver on the strategic vision of Customer-focused features and services to enhance the Client’s “Customer Service Excellence”.

Client’s Analytical Platform is a real-time, event-streaming-centric analytical platform that provides high-quality, pre-stitched 360 views of our customers, products, inventory, customer service, fulfillment, logistics and credit. The Insights Delivery Team delivers data and insights that enables Nordstrom data analysts, data scientists, leadership, store personnel and other business users to drive the critical Nordstrom customer experiences in a single place near real-time.

A Data Engineer is a key part of the Client’s Technology team that applies scientific, mathematical, and social principles to design, build, and maintain technology products, devices, systems, and solutions.

These are the technologies used in our project: Python, Spark, Kafka, Airflow, Hadoop cluster, AWS, TeraData, Tableau; GCP BigQuery, DataProc

• Data Platform Development: Design, develop, and maintain data pipelines and workflows on distributed data platforms such as BigQuery, Hadoop/EMR/DataProc, or Teradata.

• Cloud Integration: Build and optimize cloud-based solutions using AWS or GCP to process and store large-scale datasets.

• Workflow Orchestration: Design and manage workflows and data pipelines using Apache Airflow to ensure scalability, reliability, and maintainability. 

• Containerization and Orchestration: Deploy and manage containerized applications using Kubernetes for efficient scalability and resource management.

• Event Streaming: Work with Kafka to implement reliable and scalable event streaming systems for real-time data processing.

• Programming and Automation: Write clean, efficient, and maintainable code in Python and SQL to automate data processing, transformation, and analytics tasks.

• Database Management: Design and optimize relational and non-relational databases to support high-performance querying and analytics.

• System Monitoring & Troubleshooting: Participate in the on-call rotation to monitor systems, address incidents, and ensure the reliability of production environments.

• Collaboration: Work closely with cross-functional teams, including data scientists, analysts, and product managers, to understand data requirements and deliver solutions that meet business objectives.

  Participate in code reviews, technical discussions, and team collaboration to deliver high-quality software solutions

Must have:

• 2+ years of relevant Data Engineering experience

• Classical Data Warehouse, Data structures, Data marked, Data profiling

• Experience writing advanced SQL

• Experience with one of Python, Java or Scala

• ETL

• Experience with GCP BigQuery or Teradata

• Basic experience with BigData

Nice to have:

• Experience with Spark

• Other cloud computing Experience (e.g AWS)

• Knowledge of Kafka for event streaming and real-time data pipelines

• Familiarity with Kubernetes for container orchestration