About the Company
We are seeking a highly experienced Global Talent Acquisition Lead to own and scale our end-to-end hiring strategy across international markets. This role will drive the global recruitment engine, build strong talent pipelines, partner with senior leadership, and deliver high-quality hires with speed and consistency. The position requires deep expertise in India talent markets (especially Mumbai) combined with proven experience hiring across the MEA and APAC.
About the Role
Key Responsibilities
Qualifications
Required Skills
Preferred Skills
Equal Opportunity Statement
We are committed to diversity and inclusivity in our hiring practices.
Read LessRole: QA (ETL) Lead
Job Location: Mumbai (Work from Office)
Experience- 7-10 Yrs
Notice Period- 0-30 Days
Required Skills & Qualifications Experience: 5-7 years in Data Testing/Engineering, with at least 3 years in a Lead role (preferably in Fintech or Banking). Highly process oriented and lead 3-4 projects at once.
Technical Stack: Expert Level: Advanced SQL (Window functions, complex joins, stored procedures).
Data Pipelines: Deep understanding of ETL tools (Confluent Kafka, BODs, or Azure Data Factory) and Data Warehousing (Snowflake ,Databricks or ODS).
Automation: Proficiency in Python or Java for data testing automation; experience with any Data quality testing tool is a plus.
Domain: Strong grasp of Banking Data Domains (e.g., Credit Risk, Retail Banking, or Regulatory Reporting).
JD:
1. Technical Strategy & Enablement -
Design and implement a Standardized Data Validation Framework (SQL/Python) that can be applied across different sources and pipelines. Establish validation logic for ETL/ELT processes, ensuring data lineage is preserved. Automated approach for repetitive reconciliation tasks (Source-to-Target) to reduce manual effort and increase team throughput.
2. Delivery & Quality Governance -
Act as the Final Technical Sign-off for test plans and results across multiple projects. Perform root-cause analysis (RCA) on data discrepancies and schema drifts. Ensure all testing activities comply with customers' requirements as per Requirement specification. Should have proper understanding of QA project documentation and dependency.
3. Team Mentorship & Resource Levelling-
Provide technical guidance to 4-5 Junior Testers, performing code reviews of their SQL/scripts. Ensure their doubts are handled in time to reduce invalid bugs during testing.
4. Stakeholder Management-
Interface with Client Data Leads and Architects to understand pipeline build and upcoming changes. Translate technical data risks into business impact reports for the Project / Program Manager. Attend and handle Daily calls for ongoing projects for status updates and technical support along with test engineers
Read Less1. Technical Strategy & Enablement -
Design and implement a Standardized Data Validation Framework (SQL/Python) that can be applied across different sources and pipelines. Establish validation logic for ETL/ELT processes, ensuring data lineage is preserved. Automated approach for repetitive reconciliation tasks (Source-to-Target) to reduce manual effort and increase team throughput.
2. Delivery & Quality Governance -
Act as the Final Technical Sign-off for test plans and results across multiple projects. Perform root-cause analysis (RCA) on data discrepancies and schema drifts. Ensure all testing activities comply with customers' requirements as per Requirement specification. Should have proper understanding of QA project documentation and dependency.
3. Team Mentorship & Resource Levelling- Provide technical guidance to 4-5 Junior Testers, performing code reviews of their SQL/scripts. Ensure their doubts are handled in time to reduce invalid bugs during testing.
4. Stakeholder Management-
Interface with Client Data Leads and Architects to understand pipeline build and upcoming changes. Translate technical data risks into business impact reports for the Project / Program Manager. Attend and handle Daily calls for ongoing projects for status updates and technical support along with test engineers
Required Skills & Qualifications Experience: 5-7 years in Data Testing/Engineering, with at least 3 years in a Lead role (preferably in Fintech or Banking). Highly process oriented and lead 3-4 projects at once.
Technical Stack: Expert Level: Advanced SQL (Window functions, complex joins, stored procedures).
Data Pipelines: Deep understanding of ETL tools (Confluent Kafka, BODs, or Azure Data Factory) and Data Warehousing (Snowflake ,Databricks or ODS).
Automation: Proficiency in Python or Java for data testing automation; experience with any Data quality testing tool is a plus.
Domain: Strong grasp of Banking Data Domains (e.g., Credit Risk, Retail Banking, or Regulatory Reporting).
Read Less