Data Engineer
Evanston/Chicago, IL
Job Overview:
We are looking for a savvy Data Engineer to join our growing team of analytics experts.
The hire will be responsible for expanding and optimizing our data and data pipeline
architecture, as well as optimizing data flow and collection for functional teams. 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 of multiple teams, systems and products. 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.
Responsibilities for Data Engineer
- Create and maintain optimal data pipeline architecture
- Assemble large, complex data sets that meet functional/non-functional business
requirements
- Identify, design, and implement internal process improvements: automating manual
processes, optimizing data delivery, re-designing infrastructure for greater
scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and
loading of data from a wide variety of data sources using SQL
- Work with data and analytics experts to strive for greater functionality in our
data systems
Qualifications for Data Engineer
- We are looking for a candidate with 3-5 years of experience in a Data Engineer
role, who has attained a Bachelors/Masters degree in Computer Science, Statistics,
Informatics, Information Systems or another quantitative field.
- Experience performing root cause analysis on internal and external data and
processes to answer specific business questions and identify opportunities for
improvement
- Very good analytic skills related to working with unstructured datasets
- Build processes supporting data transformation, data structures, metadata,
dependency and workload management
- Experience supporting and working with cross-functional teams in a dynamic
environment
- Experience with relational SQL and NoSQL databases
- Experience building and optimizing ‘big data’ data pipelines, architectures and
data sets
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with object-oriented/object function scripting languages: Python, Java,
C++, Scala, etc.