Deeptaanshu Kumar
About
Deeptaanshu Kumar is from Washington DC-Baltimore Area. Deeptaanshu is currently Vice President of Data at Wizard AI, located in Washington DC-Baltimore Area. In Deeptaanshu's previous role as a Vice President of Data Engineering at The Arena Group, Deeptaanshu worked in Washington, District of Columbia, United States until Mar 2026. Prior to joining The Arena Group, Deeptaanshu was a Director of Data Engineering at Freddie Mac and held the position of Director of Data Engineering at Washington, DC. Prior to that, Deeptaanshu was a Manager of Data Engineering at Freddie Mac, based in Washington, District of Columbia, United States from Nov 2020 to Oct 2021. Deeptaanshu started working as Lead Data Engineer at Freddie Mac in Washington D.C. Metro Area in Oct 2019. From Jul 2018 to Oct 2019, Deeptaanshu was Principal Software Engineer at Capital One, based in Washington D.C. Metro Area. Prior to that, Deeptaanshu was a Senior Software Engineer at Capital One, based in Washington D.C. Metro Area from Jul 2016 to Jul 2018. Deeptaanshu started working as Data Engineer at Capital One in Washington DC-Baltimore Area in Jul 2015.
Deeptaanshu Kumar's current jobs
As the Head of Data at Wizard AI, I lead the Data org which comprises of the Data Engineering, Data Ops, and Data Analytics teams, and am building the core Data Platform on GCP/AWS to serve Wizard AI's Agentic AI Commerce use cases. As part of this project, I am using Big Data technologies that include: 1. Spark 2. Airflow 3. BigQuery 4. Delta Lake 5. Dataproc
Deeptaanshu Kumar's past jobs
As a member of the Data & AI Executive Leadership team, I am helping architect and build The Arena Group's Enterprise Data Platforms on both AWS and GCP. As part of this project, I am using Big Data technologies that include: 1. Databricks Lakehouse 2. Spark 3. BigQuery 4. Delta Lake 5. dbt
As a member of the Enterprise Data Services team, I helped build Freddie Mac's Cloud-Native Enterprise Data Lake in AWS to enable Data Science and other advanced business analytics capabilities. As part of this project, I implemented Big Data technologies such as: 1. Snowflake 2. Spark 3. Dremio 4. Attunity 5. Amazon EMR (Elastic MapReduce)
As a member of the Enterprise Big Data & Innovation team, I helped build Freddie Mac's first Enterprise Data Warehouse in the Cloud! During the migration from our on-prem data warehouses to the Cloud, I leveraged Big Data technologies and AWS-managed services such as: 1. Snowflake 2. Talend 3. Attunity 4. Amazon EMR (Elastic MapReduce) 5. HDP (Hortonworks Data Platform)
As a member of the Enterprise Data Platform team, I helped build Freddie Mac's Enterprise Data Ecosystem in the Cloud. In order to establish this Data Ecosystem, I used open-source, Big Data technologies and AWS-managed services such as: 1. Amazon Kinesis 2. Apache Sqoop 3. AWS Lambda 4. Amazon EMR (Elastic MapReduce) 5. Amazon Redshift 6. Amazon Athena 7. HDP (Hortonworks Data Platform)
As a member of the Customer Core team, I helped create and oversee the infrastructure for the Customer Data Management Cloud Platform that centralizes all of Capital One's customer-related data in a single platform. This was part of an initiative to enable a new customer-centric business case worth over $100MM+ in revenues. I leveraged open-source, Big Data technologies to maintain infrastructure for the Data Ingestion Spark Pipeline and Customer Data APIs. This platform migrated all of Capital One's customer-related data from existing on-premise Mainframe systems to the Cloud (AWS). The technologies and tools involved include the following: 1. Apache Zookeeper 2. Apache Kafka 3. Apache Spark 4. Apache Druid 5. Apache Cassandra 6. Terraform/Ansible 7. Spring Boot APIs
As a member of the Data Technology Strategy team, I used principles of Lambda Architecture to design and implement solutions for Capital One's various use cases. I worked on delivering a solution for a fraud detection use case using the following open-source technologies: 1. Apache Spark/Spark Streaming 2. Apache Zookeeper 3. Apache Kafka 4. Apache Hadoop 5. Apache HBase
As a member of the Enterprise Data Services team, I leveraged open-source, Big Data technologies to boost efficiency and optimize costs for business applications. I worked on building Capital One’s Cybersecurity Data Lake using the following open-source technologies: 1. Apache Hadoop 2. Apache Metron 3. Apache NiFi 4. Apache Zookeeper 5. Apache Kafka 6. Apache Storm 7. ELK stack (ElasticSearch, Logstash, Kibana)