SUMMARY

• 12+ years of Professional IT experience with Data warehousing and Business Intelligence background in Designing, Developing, Analysis, Implementation and post implementation support of DWBI applications.
• Extensive experience on Data Engineering field including Ingestion, Datalake, Datawarehouse, Reporting and Analytics.
• Strong knowledge and experience on Data Analysis, Data Lineage, Big Data pipelines, Data quality, Data Reconciliation, Data transformation rules, Data flow diagram including Data replication, Data integration and Data orchestration tools.
• Solid Experience and understanding of Implementing large scale Data warehousing Programs and E2E Data Integration Solutions on Snowflake Cloud, AWS Redshift, Informatica Intelligent Cloud Services (IICS - CDI) & Informatica PowerCenter integrated with multiple Relational databases (MySQL,Teradata, Oracle, Sybase, SQL server, DB2)
• Knowledge and experience on AWS services like Redshift,Redshift spectrum,S3,Glue,Athena, Lambda,cloudwatch and EMRs like HIVE, Presto
• Hands on Experience on Python programming for data processing and to handle Data integration between On-prem and Cloud DB or Datawarehouse.
• Experience with container based deployments using Docker, working with Docker images, Docker registries.
• Hands-On experience on Analyzing SAS ETL, Implementation of Data integration in Informatica using XML, Webservices, SAP ABAP, SAP IDoc.
• Experienced with Teradata utilities Fast Load, Multi Load, BTEQ scripting, Fast Export, SQL Assistant and Tuning of Teradata Queries using Explain plan
• Worked on Dimensional Data modelling in Star and Snowflake schemas and Slowly Changing Dimensions(SCD).
• Developed Informatica Development Standards, Best practices, Solution Accelerators and Re-usable components for design and delivery assurance.
• Pro-Active to Production Issues, punctuality in Meeting deadlines and always follow First Time Right (FTR) and On Time Delivery (OTD) approach.

TECHNICAL SKILLS

Methodologies: Agile (Scrum, Kanban), Waterfall

Database: MySQL,Teradata, Oracle, Sybase, SQL server, DB2

Cloud: Snowflake, AWS Redshift, S3, Redshift Spectrum,RDS,Glue,Athena,LambdaCloudwatch,HIVE,Presto.

Data Orchestration Tools: AWS Managed Apache Airflow(MWAA) & Splunk(logs), Snaplogic.

DevOps: Docker Images, Kubernetes Container,CI/CD Pipeline

ETL Tools: Informatica Power Center 8.x,9.x,10.x, Informatica Intelligent Cloud Services

Data Virtualization tools: Denodo

Scheduling: Active Batch, CA7,Control- Confidential

Scripts: Advanced SQL, Python, PL/SQL, Unix shell scripting, XML,JSON

Code Mgmnt process/tools: GitLab,GitHub,Bitbucket, Microsoft TFS, SourceTree

Project Mgmnt Process: JIRA,Confluence

Defect Tracking tools: HP Quality Center, Microsoft TFS

Design: Microsoft Visio.

Operating System: Windows,Linux

Business Domain: Financial, Healthcare, Hospitality, Banking, Travel, RetailInsurance,Entertainment

PROFESSIONAL EXPERIENCE

Confidential

Snowflake Data Engineer

Responsibilities:

• Worked on Architecture Design for Multistate implementation or deployment.
• Implement One time Data Migration of Multistate level data from SQL server to Snowflake by using Python and SnowSQL.
• Day to-day responsibility includes developing ETL Pipelines in and out of data warehouse, develop major regulatory and financial reports using advanced SQL queries in snowflake.
• Stage the API or Kafka Data(in JSON file format) into Snowflake DB by FLATTENing the same for different functional services.
• Build Docker Images to run airflow on local environment to test the Ingestion as well as ETL pipelines.
• Building/Maintaining Docker container clusters managed by Kubernetes. Utilization of Kubernetes and Docker for the runtime environment of the CI/CD system to build, test and deploy.
• Created Airflow DAGs to schedule the Ingestions, ETL jobs and various business reports.
• Support Production Environment and debug issues using Splunk logs.
• On call support for production job failures and lead the effort on working with various teams to resolve the issues.

Confidential

AWS Data Engineer

Responsibilities:

• Part of Architecture design to migrate current ETL jobs to Cloud using Attunity Replication,AWS Redshift and Snaplogic Framework .
• Developed Business logic in semantic layer by creating views in AWS Redshift to provide transformation logic visibility.
• Create and load staging tables based on the logic defined in views using Distribution, Sort Key’s for optimal performance.
• Part of the team to design common snaplogic pipeline to load all tables by reading meta data dynamically based on each subject area
• Collect Load Stats of Start Time, End Time, Total Records loaded and Notify production support team with load details

Confidential, Nashville, TN

AWS Data Engineer

Responsibilities:

• Perform complex transformations from different sources in AWS Redshift and Unload the result dataset into HIVE/Presto stage which is built on AWS Data lake S3.
• Builds the HIVE query with set of Applicable Parameters to load the data from HIVE/Presto Stage to Actual HIVE/Presto Target table which is again built on AWS S3 path. In Some cases, Unload of data from Stage to Target table happens through AWS RDS.
• Perform tuning of AWS Redshift SQL Queries by effectively using Appropriate Distribution Styles and Keys.
• Build Python Programming to extract data from AWS S3 and load into SQL server for one of business teams as they are not exposed to cloud.
• Creation of Business views using DENODO VDP(Virtual DataPort) and scheduling jobs using Active Batch scheduler.

Confidential

AWS Data Engineer

Responsibilities:

• Design and Develop ETL Processes in AWS Glue to migrate Campaign data from external sources like S3, Parquet/Text Files into AWS Redshift.
• Used AWS glue catalog with crawler to get the data from S3 and perform sql query operations using AWS Athena
• Create external tables with partitions using AWS Athena and Redshift
• Create a Lambda function to run the AWS Glue job based on the de ned AWS S3 event
• Created monitors, alarms, notifications and logs for Lambda functions, Glue Jobs using Cloudwatch.

Confidential

ETL Lead/ Sr.ETL Cloud Developer

Responsibilities:

• Analysed SAS ETL and Implemented the ETL logic as Informatica mappings.
• Effectively using IICS Data integration console to create mapping to consolidate and bring data into MedeAnalytics system from different source systems like Sql Server, Oracle, Flat Files.
• Develop reusable & concurrent executable workflows in IICS for SAS data extraction
• Involved in performance optimization of IICS jobs and design efficient queries to query data.

Confidential

ETL Lead/ Sr. ETL Developer

Responsibilities:

• Architect the ETL process for Migration of data from Datamart Analytix system to the Teradata Environment
• Worked on Performance constraints of the jobs using Multi Load and partition concept
• Handled history load of 5 yrs of weekly and monthly data.
• Created Teradata views with required Grant roles and user groups for different authorization level
• Created BTEQ Scripts for pre population of the work tables prior to the main load process.
• Used SQL Query optimization (explains plans, collect statistics, data distribution across AMPS, primary and secondary indexes, locking, etc.) to achieve better performance.

Confidential

ETL Lead/ Sr. ETL Developer

Responsibilities:

• Work with business owners in understanding the business requirements.
• Preparing estimations for all development and enhancement work.
• Analyze and solve business problems at their root, stepping back to understand the broader context.
• Functional testing of the developed objects.
• Performance tuning of Informatica Mappings & Pl/Sql.
• Leading and developing a team of DWBI Engineers.
• Creating all functional and non-functional requirements along with High level and Low-Level Design documents
• Establishing ETL Governance standards and best practices.
• Solution based architecture for ETL problems, unit testing strategies and development of ETL jobs for data warehouses.
• Owning end to end responsibility and accountability of each change request in terms of no requirements miss, noncompliance of process and quality of deliverable etc.