Meet the Data Architect Who Turns Complex Challenges into Streamlined Solutions!
The explosion of information generated from various sources, social media, customer interactions, sales transactions, and more, has created a complex domain that organizations must manage. This situation has made effective data management not just important but essential for strategic decision-making and long-term success. Organizations often find themselves sitting on mountains of unstructured data, which includes emails, social media posts, and multimedia files. This type of data is not easily categorized or analyzed using conventional methods. As a result, many companies struggle to extract meaningful insights from their data, leading to missed opportunities and inefficient decision-making processes.
To address these challenges, Kishore Gade, a seasoned Data Solution Architect Lead at JPMorgan Chase & Co., leverages his expertise to transform how enterprises approach data management. With over 21 years of experience, he has been at the forefront of implementing cutting-edge technologies in Enterprise Data Warehousing (EDW), the HADOOP Data Ecosystem, and AWS Data Lake applications.
His deep understanding of emerging technologies in data modeling empowers organizations to not only manage but also leverage their data effectively. Kishore’s collaborative approach allows him to work closely with business stakeholders, translating complex requirements into actionable data architecture plans.
His strategic vision has led to the development of robust database architectural strategies that align with business needs, supporting advanced analytics and machine learning models. Kishore’s passion for continuous improvement ensures that his organization remains agile and competitive in the growing market.
Let us learn more about his journey:
A Journey Through Data Mastery
With over 21 years of experience in Enterprise Data Warehousing (EDW), the Hadoop Data Ecosystem, and AWS Data Lake application implementations, Kishore has consistently evaluated emerging technologies in data modeling. This ongoing exploration has significantly enhanced the organization’s ability to manage vast amounts of information effectively.
Kishore’s expertise encompasses the end-to-end implementation of various projects, where he collaborates closely with business stakeholders. His skill in translating requirements into actionable data architecture plans has led to the development of robust database architectural strategies. These strategies are designed to meet business or industry needs, particularly in support of Data & Analytics and Machine Learning models.
His extensive experience includes working with large databases exceeding 500 terabytes, particularly in Teradata data warehousing and Active Data Warehousing. Kishore is well-versed in data warehousing methodologies such as Kimball modeling, including Star and Snowflake schemas, as well as Bill Inmon’s 3NF and ER modeling. He is also knowledgeable in Business Intelligence (BI) methodologies like ROLAP and OLAP cubes.
Kishore has a wealth of domain expertise across finance, retail, manufacturing (including inventory, supply chain, and shipping), aviation, and insurance. He has successfully implemented large-scale applications within the data warehousing ecosystem using frameworks like TOGAF and LAMDA architecture.
His strong background in regulatory reporting includes compliance with standards such as the Basel Committee on Banking Supervision (BCBS), Matters Requiring Attention (MRA), the Home Mortgage Disclosure Act (HMDA), and sustainable compliance initiatives.
Kishore is proficient in using data modeling tools like Erwin and PowerDesigner to convert functional requirements into conceptual, logical, and physical data models. His expertise extends to industry-standard data models, including the Teradata Manufacturing Logical Data Model (mLDM), Oracle Financial Services Analytical Applications (OFSAA), and IBM Banking Data Warehouse (BDW). He has developed and implemented strategies for Master Data Management (MDM), data quality, data security, and governance initiatives. His knowledge of data profiling for source data analysis and validation is supported by tools such as Wherescape 3D, Informatica IDE, and IDQ.
Kishore has also established standards for new environments involving Teradata-Informatica integrations, Hadoop Data Ecosystem practices, and AWS migration best practices. His expertise includes performance improvement and troubleshooting across various platforms, Informatica mappings, Teradata scripts, Hadoop Hive queries, AWS Glue & Athena, and end-user reporting queries.
He has successfully instantiated Erwin Semantic models into large data warehouses like Teradata and Big Data ecosystems such as HDFS and Cassandra. His work ensures that refined datasets are readily available for Machine Learning models and analytics.
Kishore employs effective error handling strategies to capture errors and maintain referential integrity during data loading processes. He automates notifications for exception records to streamline communication with source teams. Additionally, he excels in SQL and NoSQL data analytics using visualization tools like Business Objects, Cognos, Tableau, Trifacta, ATSCALE, and Alteryx. Throughout his career, he has delivered comprehensive end-to-end solutions that facilitate migrations from relational databases to Big Data platforms and ultimately to AWS Data Lakes.
His adaptability to new environments is matched by his proficiency in both Waterfall and Agile methodologies. Kishore’s analytical prowess, organizational skills, planning abilities, and interpersonal strengths have consistently positioned him as a leader within his field.
A Comprehensive Skill Set
Kishore showcases an impressive array of skills that span various domains in data management and analysis. His proficiency encompasses a wide range of tools and technologies that enable him to excel in his field.
Data Modeling and Databases
Kishore is well-versed in data modeling tools, including Erwin across multiple versions and Power Designer. His experience with relational databases is extensive, covering Oracle from versions 8i to 11g, as well as Teradata and SQL Server.
Big Data Technologies
In the realm of big data, Kishore has hands-on experience with platforms such as HDFS, Cassandra, and Hive. He is adept at utilizing tools like Spark and Airflow, along with data formats like Avro and Parquet. His familiarity with Jupyter Notebooks further enhances his capability to analyze and visualize large datasets.
Cloud Computing Proficiency
Kishore’s expertise extends to cloud platforms, particularly AWS. He is knowledgeable in managing services like S3 Datalake, VPC, and Lambda, among others. His skills in Terraform enable efficient infrastructure management in cloud environments.
Reporting and ETL Tools
He has a strong background in reporting tools such as Business Objects and Tableau, allowing him to create insightful visualizations. Additionally, Kishore is skilled in various ETL tools, including Informatica Power Center and DataStage, which facilitate seamless data integration processes.
Data Profiling and Operating Systems
Kishore employs data profiling tools like Wherescape 3D to ensure data quality. His operating system expertise spans UNIX, Windows, and macOS, showcasing his versatility across different environments.
Programming Languages and DevOps
Kishore is proficient in several programming languages including Java, Python, SQL, and PL/SQL. His knowledge of DevOps practices is evident through his experience with Jenkins, CI/CD pipelines, and various version control systems like GitHub.
Additional Tools and Technologies
Beyond his core competencies, Kishore is familiar with a variety of other tools that enhance his productivity. These include OFSAA for financial services analytics, project management tools like JIRA, and automation solutions such as Control-M. Kishore’s diverse skill set positions him as a valuable asset in any data-driven organization. His ability to navigate complex technologies while delivering impactful results makes him a standout professional in the field.
A Testament to Expertise
Kishore has built a strong foundation in cloud computing and data management through a series of notable certifications. His qualifications include:
- AWS Cloud Practitioner: This certification highlights his understanding of Amazon Web Services and cloud concepts.
- Datastax Cassandra Modelling: Kishore has gained expertise in data modeling with Apache Cassandra, a key skill for managing large datasets.
- Teradata Certified Implementation Specialist: This credential showcases his proficiency in implementing Teradata solutions for effective data warehousing.
- Certified Advanced Informatica Developer: Kishore is recognized for his advanced skills in Informatica, a leading data integration tool.
These certifications reflect Kishore’s expertise and readiness to tackle complex challenges in the field of technology.
Transforming Data Architecture
At JP Morgan Chase & Co. in Jersey City, NJ, Kishore has taken on the role of Lead Data Architect and Engineering Lead since April 2021. His expertise has been instrumental in shaping the home lending product teams, including Decision Sciences, Chase My Home (Advice, Explore, Buy & Manage), and Home Lending Origination applications. These initiatives are designed to enhance business discovery and enable self-service options for machine learning models, ultimately driving marketing efforts and supporting Home Lending Advisors in converting leads into loan originations.
Kishore has played a crucial role in defining information models that support complex data structures, utilizing NoSQL databases and domain modeling techniques. By collaborating closely with business stakeholders, cloud architects, and information architects, he has successfully translated requirements into actionable data architecture plans. This collaboration has led to the development of strategic database architectures during the modeling, design, and implementation phases to meet various business needs.
Engaging directly with customers and end-users, Kishore has streamlined data storage and retrieval processes by designing efficient conceptual, logical, and physical data models. This work has resulted in the creation of a shared semantic normalized model for home loan origination and has supported business intelligence initiatives through dimensional models optimized for reporting on the AWS S3 data lake. This data lake integrates external vendor sources like ICE-Encompass to cater to multiple stakeholders, including Operation Analytics and regulatory reporting.
Kishore has also enabled real-time analytics capabilities by designing streaming data pipelines using Amazon MSK on AWS Data Lake with internal CCB streaming solutions. His efforts have included migrating legacy systems to modern technologies that align with broader organizational goals, such as implementing an internal data pipeline framework using Java/Spark to reduce costs and improve computing efficiency.
Working alongside talented software engineers, Kishore has defined, built, and maintained robust cloud infrastructure while developing custom ETL processes for efficient data ingestion and transformation. His critical thinking skills have allowed him to break down complex problems and evaluate solutions effectively within tight deadlines in fast-paced environments.
In addition to these accomplishments, Kishore has implemented security best practices within the AWS environment to protect sensitive data and ensure compliance with industry regulations. He has defined cloud architecture for both hybrid and non-hybrid solutions while providing architectural leadership to technical teams, ensuring they deliver scalable and cost-effective solutions.
His design and deployment of scalable cloud architectures have significantly improved application performance and reliability. Kishore has successfully integrated disparate data sources into a cohesive AWS Data Lake that enhances advanced analytics capabilities and supports machine learning model consumption. Furthermore, he has developed and maintained CI/CD pipelines using Jenkins to boost deployment speed and reliability while accelerating time-to-market for new products through agile methodologies in end-to-end data engineering solutions.
Technologies Utilized
- AWS Datalake: Terraform, AWS S3, VPC
- Data Processing: GLUE, Athena, MSK
- Security: IAM, KMS
- Serverless Computing: Lambda, Event Bridge
- Monitoring: Cloud Watch
- Development Tools: CLI, Snowflake, PySpark
- Databases: Teradata 14.x, HDFS, Java/Spark, Oracle 11G
- Modeling Tools: Erwin 2021 R1
- Office Software: Microsoft Office 2010/13
- ETL Tools: Teradata SQL Assistant, HIVE
- Version Control: Bitbucket
- Project Management: JIRA
- CI/CD Tools: Jenkins, JFROG
- Development Environment: IntelliJ, Maven
- Monitoring & Logging: Splunk, Grafana
- File Transfer: Putty, Winscp
Through his extensive experience and technical prowess, Kishore continues to drive impactful changes within JP Morgan Chase’s data architecture sector.
Transforming Home Lending Data Architecture
Kishore held the position of Lead Data Architect at JP Morgan Chase & Co. in Jersey City, NJ, from September 2016 to March 2021. During his tenure, he played a pivotal role in designing and architecting home lending applications that facilitated business discovery and self-service capabilities, leveraging a range of tools including Erwin for modeling, Hive for querying, Trifacta for data wrangling, AtScale for aggregation, and Tableau for visualization. This work was essential in supporting data analytics and machine learning models.
Kishore led a team of data architects both onsite and offshore, collaborating closely with business partners to provide insights and deliverables that enhanced the Home Lending portfolio. His responsibilities included resource and demand management, where he estimated costs, forecasted needs, prioritized projects, assigned resources, and ensured timely delivery of outcomes.
He gathered requirements from business users and analysts to integrate new systems such as Empower for Home Equity loan origination and Early Resolution for servicing default loan workflows into the enterprise data models. Utilizing Erwin modeling tools on both Teradata (Integrated Customer Data Warehouse) and HDFS (Hadoop Data Ecosystem), he ensured seamless integration.
Kishore conducted thorough analyses of existing source systems, including Mortgage Servicing Package (MSP), Mortgage Processing Express, and Private Banking Loan Origination System—to identify enhancement opportunities for semantic data models that supported current applications. He also managed the migration of legacy systems like INFO1 (Legacy EDW Platform) and MBODS (Mortgage Banking Operational Data Store) to the Big Data platform.
In addition to these tasks, he designed risk data attributes to facilitate various regulatory reports such as Matter Requiring Attention (MRA), Comprehensive Capital Analysis and Review (CCAR), and Home Mortgage Disclosure Act (HMDA). His work resulted in the creation of conceptual, logical, and physical data models within the Wisdom layer that provided a unified platform for operational reporting and analytics across the Home Lending sector.
Kishore architected applications that empowered self-service capabilities through tools like Trifacta/Alteryx for data wrangling and AtScale for data aggregation. He performed detailed data analysis on source systems using Teradata SQL Assistant and Hive, identifying demographics essential for the design of physical and semantic models.
He prepared source-to-target mapping documents to secure approvals from IT stakeholders for development activities using Informatica/Ab Initio ETL design. Additionally, Kishore analyzed existing Hadoop Ecosystem metadata to create insightful monthly executive management reports using Tableau.
Working alongside data stewards from the Data Management Council (DMC), he identified critical data elements and defined new metadata attributes in line with data governance principles. He meticulously prepared documentation such as metadata classification, data mapping, and security protection assignments to ensure compliance with governance architecture standards.
Kishore also assigned data security policies within the Unified Data Services (UDS) portal to safeguard personally identifiable information (PII) from unauthorized access. He developed target state models for the Home Lending business and collaborated with the Information Architecture team to enhance conceptual designs.
His efforts included performing enterprise model integrations and clean-ups within Erwin Model Mart to adhere to data governance standards while feeding repository files into Ab Initio Metadata Repository (MDR) for user access to business attribute metadata. He implemented physical instantiation of Hive semantic models into Hive External and Optimized Row Columnar (ORC) tables for efficient consumption from the Hadoop platform.
To streamline the data modeling process further, Kishore developed an Excel utility that integrated with Erwin to enrich metadata aspects of the data models. Throughout his role, he delivered projects using Agile methodologies, ensuring adaptability and responsiveness in a fast-paced environment.
- Technologies Utilized
- Teradata 14.x
- HDFS
- Cassandra
- Oracle 11G
- Erwin 7.x/9.x
- Microsoft Office 2010/13
- Teradata SQL Assistant
- Hive
- Cognos v10.x
- Tableau
- Trifacta
- AtScale
- SVN
- JIRA
- Liquid Virtual Desktop Infrastructure (LVDI)
- Windows 2007 Enterprise OS
Kishore’s impactful contributions significantly advanced JP Morgan Chase’s home lending capabilities by optimizing their data architecture processes.
