In this opportunity, you will work with a large-scale Healthcare Payments company that processes over $200 million in payments annually. They are looking for a Senior Data Engineer to come join their BI and Advanced Analytics Team.
The Role
Design, develop and implement scalable batch/real time data pipelines (ETLs) to integrate data from a variety of sources into Data Warehouse and Data Lake
Design and implement data model changes that align with warehouse dimensional modeling standards.
Proficient in Data Lake, Data Warehouse Concepts and Dimensional Data Model.
Responsible for maintenance and support of all database environments, design and develop data pipelines, workflow, ETL solutions on both on-prem and cloud-based environments.
Design and develop SQL stored procedures, functions, views, and triggers
Design, code, test, document and troubleshoot deliverables
Collaborate with others to test and resolve issues with deliverables
Maintain awareness of and ensure adherence to Zelis standards regarding privacy.
Create and maintain Design documents, Source to Target mappings, unit test cases, data seeding.
Ability to perform Data Analysis and Data Quality tests and create audit for the ETLs.
Perform Continuous Integration and deployment using Azure Devops and Git
Technical Skills / Knowledge
Has demonstrated proficiency in designing and developing Azure Data Factory Pipelines. (2 Years)
Strong Experience designing and implementing Data Warehouse.
Experience working with Microsoft BI stack (SSIS/SSRS/SSAS) and Microsoft SQL server. (5 Years)
Must have Experience with at least one Columnar MPP Cloud data warehouse (Snowflake /Azure Synapse / Redshift) (2+ years)
Working knowledge managing data in the Data Lake.
Experience in ETL tools like Fivetran and DBT. (2 Years)
Experience with Git and Azure Devops.
Experience in Agile, Jira and Confluence.
Solid understanding of programming SQL objects (procedures, triggers, views, functions) in SQL Server. Experience optimizing SQL queries a plus.
Working Knowledge of Azure Architecture, Data Lake
Advanced understanding of T-SQL, indexes, stored procedures, triggers, functions, views, etc.