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Responsibilities for Data Engineer: • Create and maintain optimal data pipeline architecture. • Assemble large, complex data sets that meet functional / non-functional business requirements. • Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and ‘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. • Keep our data separated and secure across national boundaries through multiple data centers and regions.
We are looking for an experienced Data Engineer to support our analytics team. The hire 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. 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. Qualifications for Data Engineer • 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. • Strong analytic skills related to working with structured & 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 datasets. • Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores. • Strong project management and organizational skills. We are looking for a 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 experience using the following software/tools: • Experience with big data tools: Hadoop, Spark, Kafka, etc. • Experience with relational SQL and NoSQL databases, including Postgres and Cassandra. • Experience with data pipeline and workflow management tools: Knime, Flume, Alteryx • Experience with cloud services: EC2, EMR, RDS, Redshift, Azure, Azure SQL and Warehouse • Experience with stream-processing systems: Storm, Spark-Streaming, etc. • Experience with object-oriented/object function scripting languages: Python, Java, R
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