Lead Data Engineer
With millions of store and online guests daily, Target is now leading the effort in tearing down the walls between the traditional brick-and-mortar and web retail businesses. Just as established e-commerce giants are beginning to ramp up their physical store presence, Target is already leveraging its massive supply chain of over 1,800 stores and 38 distribution centers worldwide to deliver the best experience to its guests.But with huge amounts of both foot and web traffic comes a host of challenging problems: How do you link online and store behavior to create a cohesive view of a guest? How do you translate this heterogeneous data into actionable decisions in real-time? How can the in-store experience be enhanced by the mobile experience and vice versa?As a data engineer, you will work as part of a small team to answer these types of questions and more, all with the potential to have a very broad impact at Target. Our office combines the freedom and agility of a startup with the security and vast resources of a large established company.Requirements:
- BS degree; engineering/quantitative field.
- 2+ years academic or professional experience in application development.
- Experience building applications at scale - NoSQL, distributed file systems, and high-availability applications.
- Version control, particularly Git.
- Experience with SQL languages.
- Broad understanding of object-oriented and functional programming paradigms.
- Comfortable with at least one scripting language (e.g., bash/python).
- Comfortable in *nix environment (e.g., ssh and standard commands).
- Excellent verbal and written communication skills.
- Experience with Scala and/or Spark.
- Experience building production applications in a secure Hadoop environment.
- Experience with Kafka.
- Advanced in at least one functional programming language.
- Experience in a JVM language.
- Experience with NoSQL data stores (especially Cassandra).
- Contributions to large open-source projects.
- Master's in Computer Science or related field.
- PhD in any quantitative field.