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JD for Data Engineering positions
Location: Remote for now | Richmond, VA/Plano, Texas/Wilmington, DE/Chicago, IL (It could be any of these depending on what role they get mapped to)
Required Qualifications:
5+ years of experience (Sr-level) Strong Programming experience with object-oriented/object function scripting languages: Scala/PySpark/Python
5+ years of experience (Mid-level) Experience with big data tools: Hadoop, Apache Spark etc.
1+ years of strong technical Experience with AWS cloud services and DevOps engineering: S3, IAM, EC2, EMR, RDS, Redshift, Cloudwatch with Docker, Kubernetes, GitHub, Jenkins, CICD
Experience with stream-processing systems: Spark-Streaming, etc. (Nice to have)
1+ Years of experience with relational SQL, Snowflake and NoSQL databases, like Postgres and Cassandra.
Good communication skills, sense of ownership and open to learn attitude.
Roles/Responsibilities:
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.
Peritus Inc
