Description

•          Analyze data mapping documents and business requirements to design comprehensive test plans and cases.

•          Perform source-to-target data reconciliation, check data loading, and ensure transformation rules are applied correctly.

•          Write complex SQL scripts for validation (count, data completeness, data consistency, data truncation).

•          Identify, log, and track data defects using tools like JIRA or HP ALM or Octane.

•          Automate test scripts and validate data volume, performance, and scalability. 

•          Expert-level knowledge of SQL for data analysis.

•          Experience with tools such as Informatica and IDMC.

•          Understanding of data warehouse concepts and architectures (e.g., star/snowflake schema).

•          Familiarity with Hadoop or Spark is often preferred. 

•          Validate HiveQL, HDFS file structures, and data processing within the Hadoop cluster.

•          Strong analytical and troubleshooting skills.

•          Excellent communication for collaborating with developers and stakeholders. 

•          Knowledge in Metadata dependent ETL process and batch/job framework

Tools & Skills: 

IDMC, Informatica Power center, Hive, Kafka Knowledge, SQL, Oracle, PL/SQL

Domain: Banking knowledge, Payments knowledge preferred.

Concept: Data Warehousing, Data Transformation, ETL/ELT, Data Quality.

Key Skills

Education

Bachelor's degree