Position: Lead Java Engineer
Company: Zoolatech
Category: Java
Experience required: 5y
English level: upper

Nordstrom is on a journey from legacy batch-centric practices to a real-time, event-streaming-centric platform, Nordstrom Analytical Platform (NAP), to produce high-quality pre-stitched 360 views of our customers, product, Inventory, etc. We have laid the groundwork and are ready to take the next step in our journey and build business logic that delights our customers.
Marketing Technology Streaming Team is tasked with using data to improve the customer experience and our ability to reach people in the way they prefer with relevant information to make their shopping experience more seamless.

**Responsibilities**
- Design and develop distributed data processing pipelines in the Big Data ecosystem using Spark, Flink, Kafka, Airflow, Hive, Hbase, Presto, etc.
- Turn data into insights and connect those insights with our customers
- Collaborate with technical program management, analytics, and marketing business partners to build scalable and durable solutions that drive business outcomes
- Build data products that reduce friction to enable our marketing initiatives  to pivot quickly
- Automate manual processes where possible, including audience segmentation, triggered email, success KPIs, etc
- Continuously improve upon existing processes and solutions
- Ongoing production support of marketing data products
- Maintain high level of coding and testing standards

**Skills Required**
- Solid foundation in software engineering practices, data modeling, objected-oriented analysis and design, design patterns, and algorithms
- 5+ years of experience in at least one programming language (e.g. Python, Java, Scala)
- 5+ years of experience with MPP Databases, SQL, data modeling, data mining, and automated engineering solutions
- Experience in developing near real-time data processing solutions using Kafka, Flink, Spark Streaming (preferred)
- Knowledge of DevOps and Ci/CD
- Experience with distributed systems (Spark, AWS EMR etc)
- Experience with cloud environments (AWS or Azure)
- Bachelor in Computer Science, Engineering, or equivalent practical experience (Master’s preferred)