Roles and responsibilities:

• Design, implement and support an analytical data infrastructure providing ad-hoc access to large datasets and computing power on AWS/Azure Data Factory, and other Azure data services.

• Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL and AWS big data technologies./ Azure

• Creation and support of real-time data pipelines built on AWS/Azure technologies including Glue, Redshift/Spectrum, Kinesis, EMR and Athena OR Azure Synapse Analytics, Azure Data Lake, Azure Databricks, Azure Functions, Event Hub, and Stream Analytics.

• Continual research of the latest big data and visualization technologies to provide new capabilities and increase efficiency.

• Working closely with team members to drive real-time model implementations for monitoring and alerting of risk systems.

• Collaborate with other tech teams to implement advanced analytics algorithms that exploit our rich datasets for statistical analysis, prediction, clustering, and machine learning.

• Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers.

Basic Qualifications

• 4-6 years of industry experience in software development, data engineering, business intelligence, data science, or related field with a track record of manipulating, processing, and extracting value from large datasets.

• Demonstrated strength in data modeling, ETL development, and data warehousing.

• Experience using big data processing technology using Spark.

• Knowledge of data management fundamentals and data storage principles

• Experience using business intelligence reporting tools (Tableau, Business Objects, Cognos, Power BI etc.)/ Hands-on experience with big data processing frameworks such as Apache Spark using Azure Databricks.