Remote Lead Data Engineer (Austell, GA)

Remote Lead Data Engineer

Remote Lead Data Engineer needs 7 years experience as data engineer in consumer finance or equivalent industry (consumer loans collections servicing optional product and insurance sales)Remote Lead Data Engineer requires Strong background in math statistics computer science data science or related discipline Advanced knowledge one of language Java Scala Python C Production experience with HDFS YARN Hive Spark Kafka Oozie Airflow Amazon Web Services (AWS) Docker Kubernetes Snowflake Proficient with Data mining programming tools (e.g. SAS SQL R Python) Database technologies (e.g. PostgreSQL Redshift Snowflake. and Greenplum) Data visualization (e.g. Tableau Looker MicroStrategy) Comfortable learning about and deploying new technologies and tools. Organizational skills and the ability to handle multiple projects and priorities simultaneously and meet established deadlines. Good written and oral communication skills and ability to present results to non-technical audiences Knowledge of business intelligence and analytical tools technologies and techniques. Familiarity and experience in the following is a plus AWS certification Spark Streaming Kafka Streaming Kafka Connect ELK Stack Cassandra MongoDB CI CD Jenkins GitLab Jira Confluence other related tools Remote Lead Data Engineer duties Responsible for identifying relevant data and utilizing data tools technologies and processes to develop continuous data driven and automated customer communications across marketing and servicing towards omni channel personalized customer experience vision and outcomes. Create and manage cloud resources in AWS Data ingestion from different data sources which exposes data using different technologies such as RDBMS REST HTTP API flat files Streams and Time series data based on various proprietary systems. Implement data ingestion and processing with the help of Big Data technologies Data processing transformation using various technologies such as Spark and Cloud Services. You will need to understand your part of business logic and implement it using the language supported by the base data platform Develop automated data quality check to make sure right data enters the platform and verifying the results of the calculations Develop an infrastructure to collect transform combine and publish distribute customer data. Define process improvement opportunities to optimize data collection insights and displays. Ensure data and results are accessible scalable efficient accurate complete and flexible Identify and interpret trends and patterns from complex data sets Construct a framework utilizing data visualization tools and techniques to present consolidated analytical and actionable results to relevant stakeholders. Key participant in regular Scrum ceremonies with the agile teams