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Company Description The primary responsibility of Senior Data Management Engineer is to build data pipelines, model and prepare data, perform complex data analysis to answer Business questions, build and automate data pipeline and quality framework to enable and promote self service data pipelines, assist in operationalizing the AI / ML Engineering solutions. This role is expected to lead and guide other team members and evangelize the design patterns as well as coding standards. What Will You Be Doing? Team up with the engineering teams and enterprise architecture (EA) to define standards, design patterns, accelerators, development practices, DevOps and CI/CD automation Create and maintain the data ingestion, quality testing and audit framework Conduct complex data analysis to answer the queries from Business Users or Technology team partners either directly from Analysts or stemmed from one of the Reporting tools such as PowerBI, Tableau, Looker etc. Build and automate the data ingestion, transformation and aggregation pipelines using Azure Data Factory, Databricks / Spark, Snowflake, Kafka as well as Enterprise Scheduler tools such as CA Workload automation or Control M Setup and evangelize the metadata driven approach to data pipelines to promote self service Setup and continuously improve the data quality and audit monitoring as well as alerting using applications such as Sod. Constantly evaluate the process automation options and collaborate with platforms engineering as well as architecture to review the proposed design. Demonstrate mastery of build and release engineering principles and methodologies including source control, branch management, build and smoke testing, archiving and retention practices Adhere to and enhance and document the design principles, best practices by collaborating with Solution and in some cases Enterprise Architects Participate in and support the Data Academy and Data Literacy program to train the Business Users and Technology tea