Analytics Data Engineer - QuantumBlack Chicago Apply Now Qualifications Meaningful experience with at least two of the following technologies Python, Scala, SQL, Java Commercial client-facing project experience is helpful, including working in close-knit teams Ability to work across structured, semi-structured, and unstructured data, extracting information and identifying linkages across disparate data sets Meaningful experience in multiple database technologies such as Distributed Processing (Spark, Hadoop, EMR), traditional RDBMS (MS SQL Server, Oracle, MySQL, PostgreSQL), MPP (AWS Redshift, Teradata), NoSQL (MongoDB, DynamoDB, Cassandra, Neo4J, Titan) A confirmed ability in clearly communicating complex solutions Deep understanding of Information Security principles to ensure compliant handling and management of client data Experience and interest in Cloud platforms such as AWS, Azure, Google Platform or Databricks Confirmed experience in traditional data warehousing / ETL tools (Informatica, Talend, Pentaho, DataStage) Flexibility to travel regional or internationally up to 80 PERCENT depending on client and base location.
Extraordinary attention to detail Who You'll Work With As a Data Engineer at QuantumBlack in Chicago, you will be working on the frameworks and libraries that our teams of Data Scientists and Data Engineers use to progress from data to impact.
Who you are You are a highly collaborative individual who is capable of laying aside your own agenda, listening to and learning from colleagues, challenging thoughtfully and prioritising impact.
You search for ways to improve things and work collaboratively with colleagues. You believe in iterative change, experimenting with new approaches, learning and improving to move forward quickly.
What You'll Do You will be working on the frameworks and libraries that our teams of Data Scientists and Data Engineers use to progress from data to impact.
We are passionate about life-long learning and professional development individual to each of our employees. Role responsibilities Work with clients to model their data landscape, obtain data extracts, and define secure data exchange approaches Plan and deliver secure, good practice data integration strategies and approaches Acquire, ingest, and process data from multiple sources and systems into Big Data platforms Create and manage data environments in the Cloud Collaborate with our data scientists to map data fields to hypotheses and curate, wrangle, and prepare data for use in their advanced analytical models Have a strong understanding of Information Security principles to ensure compliant handling and management of client data This is a fantastic opportunity to be involved in end-to-end data management for bleeding edge Advanced Analytics and Data Science