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We’re looking for a Data Engineer who lives and breathes data to join our development team. The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.
Data is key for Kramer’s growing strategy. You’ll be leading and taking part of making sure our data is being collected, processed and stored in a scalable way and that processes are working smoothly.
If you’re motivated by making a business impact, building something big and meaningful (deployed across many universities worldwide) and you have amazing data skills and passionate to grow them even more, this job is for you.
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience building and optimizing data pipelines, architecture, and data sets
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with unstructured datasets.
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
- Strong project management and organizational skills.
- We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift
- Experience with stream-processing systems: Storm, Spark-Streaming, etc.
- Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.