Job Description
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience building and optimizing big data, 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.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• A successful history of manipulating, processing and extracting value from large disconnected datasets.
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
• Experience supporting and working with cross-functional teams in a dynamic environment.
We are looking for a candidate with 3 - 6 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 experience using the following software/tools:
• Develop and improve the current data architecture using AWS Redshift, AWS S3, AWS Aurora (Postgres),Spark, AWS Glue and Hadoop/EMR.
• Improve upon the data ingestion models, ETL jobs, and alarming to maintain data integrity and data availability.
• Experience with relational SQL and NoSQL databases including MySQL and MongoDB.
• Experience with data pipeline and workflow management tools like Airflow, etc.
• Experience with stream-processing systems: Kinesis, Spark-Streaming, etc.
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc
• Strong project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment.
