Senior Data Engineer

Summary

Join Rackspace Technology as a Data Engineer and collaborate with customers to gather requirements and understand their business processes. You will create and maintain optimal data pipeline architecture, assemble large datasets, and identify and implement process improvements. Responsibilities include building infrastructure for data extraction, transformation, and loading using various technologies, building analytics tools, and deploying and monitoring systems. This role requires significant experience with big data technologies, SQL, and various software tools. Rackspace Technology offers a positive work environment and is committed to equal employment opportunity.

Requirements

• Demonstrate knowledge and real-world experience on Big data technologies. A successful history of manipulating, processing and extracting value from large datasets
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
• Strong analytic skills related to working with unstructured datasets
• Experience building and optimizing ‘big data’ data pipelines, architectures and data sets
• We are looking for a candidate with > 3+ years of experience in a Data Engineer role
• Experience with big data tools: Hadoop, Spark, Kafka, etc
• Experience with relational SQL databases such as Oracle, SQL Server, MySQL or Postgres
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc
• Experience with stream-processing systems: Storm, Spark-Streaming, etc
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc

Responsibilities

• Collaborate with customer to gather requirements and to understand their business processes
• 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 Spark, SQL and Azure or AWS 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
• Use tools to deploy and monitor the performance of the systems in production

Preferred Qualifications

For senior data engineers also should have demonstrable experience in Project management and organizational skills