Yashpalsinh Jadeja

<p>Worked with Business and Data analyst to figure out ingestion requirements.<br>
Created Dimensional Data models with the help of Star Schema.<br>
Created data ingestion pipelines to ingest data from Salesforce Financial Service Cloud(FSC) with Semantic data modeling.<br>
Used Google Doc AI for document parsing.<br>
Created Servicenow to BigQuery connection to bring in Incident details to DWH.<br>
Worked with Cloud Composer to set up the ingestion pipelines.<br>
Used DataFlow and DataForm for preparing data for reporting purpose.<br>
Created Data Fusion pipelines.<br>
Saved more than 25% GCP cost by optimizing schedules and SQL performance.<br>
Also optimized Airflow DAGs to reduce cost.<br>
Applied column level policy tags into bigquery for data governance.<br>
Used Data Catalog and Collibra as UDC.<br>
Help with migration of some of the existing GCP pipelines to Azure Databricks.</p>

<p>Created data flow diagram to migrate existing components to GCP environment.<br>
Created Data Architecture to move PySpark bill payee prediction model to GCP environment.<br>
Used Spark SQL and BQ SQL for analytics and reporting.<br>
Created Architecture diagram to migrate Spark Workloads to GCP BQ.<br>
Worked with Google cloud team to help setup Vertex AI playground for ML operations (MLOps) team.<br>
Worked with Power BI data flow and dashboard design.<br>
Experimented with various LLM models, PaLM, Bloom (huggingface) and GPT.<br>
Created Container image of open source LLM (Bloom) to use it onto Vertex AI.<br>
Worked with Vertex AI workbench and model garden and created AI workflow.<br>
Used cloud datastream to replicate onrprem Postgres data to Alloy DB.<br>
Used Looker to develop Explore and views and created Look and dashboard.<br>
Used DBT to transform data from one of the Teradata/Informatica sources to BQ.<br>
Helped team improve Airflow environment to use environment variable and streamlined the git version control.</p>

<p>Worked with Data ingestion team to ingest data into BigQuery from Legacy SAP environment, have also worked on cleansing and preparing data for business use.<br>
Used SQL Window functions and Analytics functions to create Type 2 slowly changing dimension for account and customer data in Bigquery.<br>
Build Entity relationship diagram with ERWIN, created Data flow diagram.<br>
Used different dimensional techniques (like Star Schema) to build models for business use (Fact-Dimensions).<br>
Data Curation and Data transformation.<br>
Created Tables, Views, Stored Procedures on GCP BigQuery and its DAG (Cloud Composer-Airflow) to automate it in higher environments.<br>
Build BigQuery stored procedures to replace SAS procedures.<br>
Used Looker for reporting.<br>
Worked with data governance team to define data classification and availability of data in lower environments through security views.</p>

<p>Worked as part of BMO’s Financial Crimes Unit and AML data team.<br>
Data Lead for Fraud modernization project of BMO, we have revamped Fraud architecture to have real time Fraud detection.<br>
Used data transfer services (DTS) to transfer data from on Prem Hadoop cluster to GCP BigQuery to build data warehouse on GCP.<br>
Used Dataform for data transformation and Looker for data Vizualization.<br>
Worked with big data analytics using SQL, Hive QL, GCP BigQuery.<br>
Build various data pipelines using GCP Data flow / Dataproc and PubSub.<br>
Used Docker and Containers to help AIDox team enhance their micro-services by adding latest version of Tesseract-OCR.<br>
Used Neo4j graph database for fraud detection.<br>
Used Power BI for BI dashboards.<br>
Used Google Cloud DLP (Data Loss Prevention) to identify key PCI and PII data.<br>
Created POC pipeline in AWS Lake Formation and Databricks for data migration.<br>
Worked with IBM Safer payments (AI/ML) tool to help us detect fraud in Near Real time.<br>
Worked with business partners to identify all features requirements to have new AI/ML tool working for us.</p>

<p>Interacted with internal stakeholders to understand the reporting needs and to collect requirements, design, and build reporting solutions.<br>
Investigated and identified data quality problems and implemented solutions that address root causes of the issues.<br>
Used Tableau for data exploration.<br>
Focused on big data analytics using SQL, Python, and Hadoop (HDFS, Hive, Sqoop).<br>
Analyzed and interpreted large semi-structured or structured datasets to provide business insight.<br>
Used Pandas and Numpy for data cleansing and wrangling.<br>
Created automated reports and dashboards for different Lines of Business.<br>
Created technical documentations in support of the development processes.<br>
Worked with Akora (TD Hadoop ecosystem) to move data from Enterprise data warehouse (EDW) to HDFS.</p>

<p>Designed, built, integrated data from various RDBMS sources (SQL server, DB2, Oracle) and maintained optimal data pipeline architecture.<br>
Responsible for data mapping between various source system.<br>
Expertise with Pandas and Numpy for data transformation.<br>
Used Apache Hive and Impala to access data from hive tables.<br>
Used Apache Zeppelin notebook for interactive queries.<br>
Worked with HDFS, Hive, Hadoop and PySpark to produce business reports.<br>
Used PySpark to extract, manipulate, aggregate and join various data formats including Text, JSON and XML.</p>

<p>Data manipulation/transformation using Cobol programs to match source data (various files) to the target database schema.<br>
Extract, transform and load host application data to DB2 database.<br>
Discuss technical design with teams, BAs and rectify as per change in business requirement.<br>
Data extraction and manipulation in Mainframe environment.<br>
Facilitating Product Owner and team to create user story by breakdown of epics<br>
Extracting Burn down chart and Progress reports from Jira<br>
Collaborate with geographically and culturally diverse cross-functional teams</p>

<p>Develop high-level design and code for user stories, Aware of insurance process flow starting from Quote, Cover Note and Policy.<br>
Used Python Scripts for website analysis and testing.<br>
Used Unix shell scripts.<br>
Learned open source automation tools like selenium, Hadoop and Spark to assist in legacy Modernization project.<br>
Worked with data warehouse team to extract data as per project requirement.</p>

<p>Coding and unit testing of COBOL-DB2-online transactional IMS programs.<br>
Coordinating regression and integration test of newly developed code.<br>
Responsible for Database Design and providing DBA instructions with Database artifacts.<br>
Used complex SQL queries to access DB2 databases.<br>
Worked on various production issues to perform duty of production support analyst.<br>
Used IMS database for merchant side payment application of AMEX.<br>
Evaluates and operates the day-to-day activity with third party vendor.<br>
Responsible for producing architecture artefacts for small to mid-sized applications.</p>