A Seasoned Data Specialist With Over 6 Years Of Extensive Experience Aligning Product & Customer Focussed Priorities With Technology.
Overview
6
6
years of professional experience
Work History
Data Specialist
Coforge - Ameriprise
09.2023 - Current
Consulting An Existing Team Of Informatica Developers With Their Cloud Adoption Initiative
Assisting Them In Creating Data Pipelines Leveraging Pyspark
Alongside Creating A Serverless Data Ingestion Framework Leveraging AWS - S3, Lambda, SQS, SNS, EMR, Glue, Athena, Redshift Which Will Be Used To Submit Those Pipelines.
Sr. Data Engineer
Visa Inc.
10.2021 - 08.2023
We Migrated Legacy Code From Hive to Spark Leveraging Python For A Critical Product (CAMP - Clearing & Authorisation Matching Process) Which Is A High Revenue Generating Product For Visa Where Card Acquirers & Issuers Are Charged Penalties For Erroneous Transactions
Accumulated Prowness In Building Reliable Big Data Platforms Scaled Across Multiple Data Centers
We Implemented Cycle Watcher For Anomaly Detection In Batch and Streaming Processing Applications, Improving The Agility Of Workloads And Ensuring Data Integrity & Reliability
We implemented Data Quality Audit Pipelines Across Multiple Data-Centers To Assure Data Accuracy And Consistency, Maintaining The Integrity Of Data In Visa's Data Warehouse
We Implemented Application Execution Checks Across Multiple Data Centers To Assure The Service Reliability Of Data Pipelines Running Over Different Data Orchestrators And Schedulers: Airflow, BMC Control-M
We Implemented Multiple Observability Dashboards Using Grafana & Prometheus
A One-Stop Solution To Efficiently Observe Key Application Performance Indicators Like Application Execution Statuses, Data Audit Checks, Anomaly Detection, Delay Detection, Upcoming SLAs/OLAs, Planned & Unplanned Outages/Changes, Priority Incidents, Research Requests, Upcoming Bug Fixes, Roaster Status, Escalation Metrics, etc.
Senior Analyst
Publicis Sapient - Capital Group
05.2018 - 10.2021
We Developed A Data Ingestion & Curation Framework (LASR - Load, Analyze, Store, Report) Alongside A Data Bridging Framework Using Python & MFT Architecture For a Cloud Migration Initiative Adopted By The Firm
The Data Ingestions/Curations Were Based On A Configuration Approach Where JSON Files Were Parsed And Validated To Create An Ingestion/Curation Data Model Which Was Then Stored In MySQL And Acted As An Entry Point For The Framework
At Runtime The Service Would Retrieve Data Points From MySQL And Run The Ingestion-Curation Processor Accordingly Which Was Further Built Leveraging Pyspark
Output Parquet Files Where Then Exposed On Azure Synapse Using External Tables For BI Tools Like Tableau & Power BI To Run Batches Of Critical Reports (Published Both For Marketing & Investment Management Side Of The Firm ) Also, We Later Created Deployment Pipelines (Based On The Flyway DB Model) For HQL & SQL Scripts Used In The Framework
I Also Had A Brief Exposure To ADF Where The Use Case Was Extracting Data From Salesforce Cloud And Creating Published Versions Of The Data For LASR Framework To Consume & Ingest Into Azure Synapse.