Key Responsibilities:
Design develop and optimize ETL processes for large-scale data pipelines
Develop and maintain complex SQL queries stored procedures and dynamic SQL scripts using Oracle and SQL Server
Write and maintain Python scripts and libraries for automation and data processing
Build and execute automated testing frameworks using Robot Framework and Selenium
Compare and validate large datasets using Python and SQL
Work with data storage and processing platforms like HDFS Hive and Dataiku
Perform data modeling create ER diagrams and implement data quality rules
Understand and apply database concepts (indexes constraints normalization)
Access and interpret application logs and execute Unix/Linux shell commands for troubleshooting
Collaborate in an Agile environment using tools like GitHub Jira and SSMS
Contribute to architecture and technical design for end-to-end solutions: UI API endpoints and backend logic
Implement business logic using a combination of SQL and Python
Document technical specifications and maintain reusable code libraries
Nice-to-Have Experience:
Building workflows and data pipelines with Dataiku recipes (Python/SQL)
Developing frontend interfaces using and managing APIs via APIGEE
Exposure to enterprise tools such as Workday SAP ServiceNow
Developing Tableau dashboards and reusable workbooks
Working knowledge of API endpoint development using Python
Tools & Technologies:
Languages: Python SQL Shell Scripting
Databases: Oracle SQL Server Hive
Platforms: Dataiku HDFS GitHub OpenShift
Testing: Selenium Robot Framework
Methodologies: Agile DataOps
Other Tools: Tableau SSMS APIGEE