About the Role
Create and maintain optimal data pipeline architecture
Assemble large, complex data sets that meet functional / non-functional business requirements
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 GCP ‘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
Requirements
We are looking for a savvy Data Engineer with 3-6 year experience to join our growing team of analytics experts. You will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross 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.
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 ‘big data’ data pipelines, architectures 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
Build processes supporting data transformation, data structures, metadata, dependency and workload management
A successful history of manipulating, processing and extracting value from large disconnected datasets
Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores
Experience supporting and working with cross-functional teams in a dynamic environment
Experience with one object-oriented/object function scripting languages (Python, Java, Scala, etc)
Experience with big data tools: Hadoop, Spark, Kafka, Apache beam etc
Experience with relational SQL and NoSQL databases, including Postgres and Cassandra
Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
