Austin, TX, USA
icrunchdata Network
The full-time will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flows. 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, 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 demonstrating lifelong learning and collaboration to support our next generation of products and data initiatives. 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, Databricks and AWS -big data- technologies. 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 AWS regions. 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.Qualifications for Data Engineer Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. 5 years of experience in a Data Engineer role. Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases. Experience with big data tools: Hadoop, Spark (preferably Databricks), Kinesis, etc. Experience with relational SQL databases, including Snowflake and Postgres. Experience with stream-processing systems: Spark-Streaming, etc. Experience with object-oriented/object function scripting languages: Scala, Python etc. Experience with data pipeline and workflow management tools: Jenkins, Airflow, etc. Experience with AWS cloud services: EC2, RDS, etc. Experience building and optimizing -big 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. 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- stores. Strong project management and organizational skills. Experience supporting and working with cross-functional teams in a dynamic environment. – provided by Dice [...]