As a Data Engineer - DataOps, you are responsible for creating and maintaining software development lifecycle activities pertaining to the business applications. You will design, code, test, debug, and document existing and new enhancements.

Responsibilities: 

Partner with data engineering, and business teams to set KPIs, SLAs, and SLIs for the quality and availability of data. Validate the data pipeline executions to ensure that they are completed within the SLA’s. Troubleshoot issues related to data pipelines, data integrations, bug fixes, performance bottlenecks. Work with multiple cross functional teams like Data Engineering, Business Analytics, IT and Vendor Support to resolve any incidents / problems. Continuously monitor and alert for any anomalies in the data. Implement role-based security, including AD integration, security policies, and auditing across the data platform environment. Test data to make sure it matches business logic and meets basic operational thresholds. Work with Data Scientists to support the AI / ML model development environments and operationalization of the models. Closely monitor and optimize the data platform infrastructure cost. On-call support for P1 issues on weekends / holidays on rotation basis. A desire to work in a collaborative, intellectually curious environment.

Qualifications:

A bachelor's degree in computer science or equivalent 5+ years of experience as a Data Engineer, Experience with Azure big data tools: Azure Databricks, Azure Synapse, HDInsight, ADLS Experience with relational SQL and NoSQL databases. Excellent problem solving and analytic skills associated with working on structured and unstructured datasets using Azure bigdata tools. Experience with data pipeline and workflow management tools: ADF and Logic Apps Experience with Azure cloud services: VM, Azure Databricks, Azure SQL DB, Azure Synapse Experience with stream-processing systems: Azure Streams Experience with scripting languages Python. and have strong knowledge in developing Python notebooks.