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.
Work with data and analytics experts to strive for greater functionality in our data systems.
Bachelor’s degree in Computer Science Engineering, Data Analytics, or a related technical degree.
5+ years of experience working with distributed data technologies (e.g. Hadoop, MapReduce,
Spark, Kafka, Flink etc) for building efficient, large-scale ‘big data’ pipelines.
Strong Software Engineering experience with proficiency in at least one of the following programming languages: Java, Python, Scala or equivalent.
Implement data ingestion pipelines both real time and batch using best practices.
Experience with building stream-processing applications using Apache Flink, Kafka Streams or
Experience with Cloud Computing platforms like Amazon AWS, Google Cloud etc.
Build processes supporting data transformation, data structures, metadata, dependency and
Experience supporting and working with cross-functional teams in a dynamic environment.
Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
Ability to work in a Linux environment.