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 working experience using the following software/tools:
- 3+ years of experience (Mid-level) Strong Programming experience with object-oriented/object function scripting languages: Python
- 3+ years of experience (Mid-level) Experience with big data tools: Hadoop, Apache Spark, Kafka, etc
- 1+ years of experience Experience with AWS cloud services: S3, EC2, EMR, RDS, Redshift
- Experience with stream-processing systems: Storm, Spark-Streaming, etc. (Nice to have)
- 1+ Years of experience Experience with relational SQL, Snowflake and NoSQL databases, including Postgres and Cassandra.
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 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.