Job
Description
5--7+ years experience as data engineer in consumer finance or equivalent industry (consumer loans, collections, servicing, optional product, and insurance sales) 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 Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services (AWS), Docker / Kubernetes, Snowflake 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 Proficient at developing queries, writing reports and presenting findings Mentor junior members and bring best industry practices Sound knowledge of AWS Glue, AWS Lambda, Python, PySpark
