About the Role
Create and maintain optimal data pipeline architecture.
Assemble large, complex data sets that meet functional / non-functional business requirements processes, optimising 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 utilise 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 optimising our product into an innovative industry leader.
Work with data and analytics experts to strive for greater functionality in our data systems.
Requirements
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.
At Hypefast, we are committed to creating a diverse and inclusive workplace. We believe that diverse perspectives drive innovation and excellence. We welcome candidates from all backgrounds and employment is decided on the basis of qualifications, merit, and business need.
