Primary Role Function:
- Create and maintain optimal data pipeline architecture,
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Experience with AWS cloud services: EC2, Glue, RDS, Redshift
- 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: Azkaban, Luigi, Airflow, etc.
- Experience with object-oriented/object function scripting languages: Python.
- 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.
- 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.
- Writes high quality and well-documented code according to accepted standards based on user requirements
Knowledge:
- Thorough in-depth knowledge of design and analysis methodology and application development processes
- Exhibits solid knowledge of databases
- Programming experience with extensive business knowledge
- University degree in Computer Science, Engineering or equivalent industry experience
- Solid understanding of SDLC and QA requirements
Iris is a professional software services organization offering high-quality, cost-effective solutions to businesses. It has helped meet the IT requirements of companies ranging from those among the Fortune 100 to medium-sized firms by utilizing best-of-breed technologies, rapidly deployable solution...