|
Exact Job Location/Work Address
|
Requirements are scattered across 4 main locations: Richmond VA, McLean, VA, Wilmington, DE,
Chicago, IL
|
|
Required Technologies
|
- Strong Programming experience with object-oriented/object
function scripting languages: Python, PySpark, Scala, etc.
- Experience with big data tools: Hadoop, Apache Spark,
Kafka, etc.
- Experience with AWS cloud services: S3, EC2, EMR, RDS,
Redshift
- Experience with stream-processing systems: Storm,
Spark-Streaming, etc.
- Experience with relational SQL, Snowflake and NoSQL databases,
including Postgres and Cassandra.
|
|
Job Description:
Detailed overview of functional and technical role expectations
|
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 working
experience using the following software/tools:
- Strong Programming experience with object-oriented/object
function scripting languages: Python, PySpark, Scala, etc.
- Experience with big data tools: Hadoop, Apache Spark,
Kafka, etc.
- Experience with AWS cloud services: S3, EC2, EMR, RDS,
Redshift
- Experience with stream-processing systems: Storm,
Spark-Streaming, etc.
- Experience with relational SQL, Snowflake and NoSQL
databases, including Postgres and Cassandra.
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 and AWS ‘Big data’ technologies.
- Build analytics tools that utilize the data pipeline to
provide actionable insights into customer acquisition, operational efficiency
and other key business performance metrics.
- Work with stakeholders including the Executive,
Product, Data and Design teams to assist with data-related technical
issues and support their data infrastructure needs.
- Create data tools for analytics and data scientist team
members that assist them in building and optimizing our product into an
innovative industry leader.
|
