Data Architect

Role & Responsibilities: Leading the team of 5-6 members and taking care of SLA, KPI management, etc. ETL & Data pipeline development Resolving pipeline failures to incorporate new datarequests Building new data pipelines based on best practices design patterns Optimizing legacy pipelines to align with current best practices Maintaining documentation on pipeline configurations Skills: Python, SQL, PySpark, Azure Databricks, Data Pipelines SQL: Great skills on T-SQL, stored procedures troubleshooting and development, schema management, data issues analysis, query performance analysis. Python: Intermediate development knowledge – skillful in data frames, Panda's library, parquets management, deployment on cloud. Databricks: PySpark and data frames, azure databricks notebooks management and troubleshooting, Azure databricks architecture. Azure Data Factory/ADF/Synapse/ Data Explorer: Data pipelines design and troubleshooting, Azure Linked services management.