Kishore K

Experienced data professional with expertise in ETL tools, including IBM DataStage and Azure Data Factory. Proficient in managing databases such as DB2, Oracle 10g, Snowflake, and PostgreSQL across various operating systems like AIX, Linux, and Mac. Committed to leveraging technical skills to drive data-driven solutions and enhance organisational efficiency.

Data Engineer | Freedom Mortgage

Technologies: Snowflake, SnapLogic, Oracle, Control-M

• Migrated legacy ETL processes from IBM DataStage and Oracle to cloud-based Snowflake and SnapLogic pipelines.
• Analyzed and converted complex DataStage job logic into Snowflake SQL transformations.
• Built and scheduled cloud integration pipelines and batch workflows using Control-M.
• Performed end-to-end data reconciliation between Oracle and Snowflake, ensuring 100% data accuracy.
• Supported legacy system decommissioning after successful parallel runs.

Sr Datastage Developer | IMF

Technologies: Azure Data Factory, Oracle, SQL Server, DataStage

• Supported enterprise migration from DataStage 11.7 to Azure Data Factory (ADF).
• Partnered with ADF teams to translate DataStage ETL logic into ADF pipelines and activities.
• Assisted in data ingestion from Oracle to SQL Server using Azure-native services.
• Conducted data comparison and validation between UAT and target SQL Server environments.
• Helped rebuild cloud-based Data Warehouse layers using ADF pipelines.

Datastage Developer | AB – Analytics Platform

Technologies: DataStage, Oracle, DB2, Flat Files

• Developed ETL pipelines integrating data from multiple heterogeneous sources.
• Built Data Warehouse and Data Mart structures to support analytics and reporting.
• Delivered curated datasets to enable trade marketing and retail performance analytics.

• Designed and delivered end-to-end ETL/ELT solutions using IBM DataStage and Azure Data Factory (ADF) to support enterprise data integration and cloud migration initiatives.
• Developed and maintained ADF pipelines, datasets, linked services, triggers and parameterised frameworks to enable scalable and reusable data ingestion.
• Ingested data from multiple heterogeneous sources including Oracle, SQL Server, flat files and cloud data stores, performing data cleansing, transformation and validation.
• Migrated legacy DataStage ETL logic to Azure Data Factory, converting transformations into optimised SQL queries and ADF Mapping Data Flows.
• Designed, developed and optimised complex SQL Server queries and stored procedures, improving data load performance and query efficiency.
• Applied dimensional data modelling techniques (star and snowflake schemas) to design Data Warehouse and Data Mart structures for reporting and analytics.
• Implemented full and incremental data loads using watermarking, control tables and ADF scheduling mechanisms.
• Conducted data profiling, source-to-target mapping and reconciliation to ensure data accuracy, completeness and integrity.
• Monitored and supported ADF pipelines and ETL workflows, identifying and resolving failures and performance bottlenecks.
• Implemented logging, error handling, retry policies and monitoring to ensure stable and reliable production pipelines.
• Worked closely with business analysts, cloud teams and stakeholders to translate business requirements into effective Azure data solutions.