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Las Vegas, NV.***** • 510-***-**** Mahathi • ad3ole@r.postjobfree.com com • https://www.linkedin.com/in/mahathikuchi LEADERSHIP SUMMARY

à A leader with experience in building data pipelines and solving for data+AI challenges. à A visionary in data strategy with innovative engineering towards automation, optimization and monetization, and a panache for nurturing talent. à A hands-on leader for multiple functional teams revamping end-to-end technical ecosystems to maximize availability, optimize throughput and enable data-driven culture. à A leader experienced in strategizing and leading cross-functional teams to bring about fundamental change via process and project management, leadership and mentoring. à My strengths highlight strategic vision and a grit for accomplishing evolutionary projects. à

FUNCTIONAL FORMAT

Experience at Director Level: 6 years

AMERICAN A leader, as SPECIALTY a part of transformational HEALTH: 2020 revolution - 2021 at ASH, accomplished the following goals. à Modernized code cloud. modularized the data logic platform as part via of migrating metadata the based data automated platform orchestration, from on premise low-to code-Azure no- à Improved hours or less. time-to-market by 10-fold reducing building of new data model and assets to 4 à Curated the 3 Vs team of data transition engineering, to PySpark Velocity, data Volume processing and Veracity. in Azure cloud towards improvement of à Provided to Azure cloud leadership supporting and project enterprise management analytics. support to migrate three large data contexts à Provided literacy and guidance promoting and leadership the self-service to Data DaaS. Governance enterprise initiative evangelizing data à Evangelized teams. modern cloud mechanisms and orchestration methods with cross-functional à Redesigned Azure harbinger Devops for the the QA QA team pipelines process to adopt for conducting data the CI/platform CT/unit, CD component to process include for automated and future functional releases. testing testing. framework This is via a à Established coding best practices for on premise and cloud related coding languages. à Redesigned code and data elements organization and established naming convention and 2

nomenclature for data platform.

à Developed such future cover Data Science as production resiliency Power automated projects Automate projects issues. slated data This to and delivery, for preserve framework Microsoft the approval future. platform Bot can and framework. also stability notification help by with This introducing architecture artificial were to auto-intelligence become using healing Power a base for bots apps the for to à Eliminated teams platform. through 50% two of technical rounds of debt performance on data platform tuning and by incorporating re-engineered best the practices, ELT on the guided data à Streamlined database design multiple to optimize data models on premise and data common platforms. data elements such as date format and à Revamped training and process cloud to certification. mentor, train and empower team members to upskill and innovate via SNAPFISH: In and the strengths role 2017 of to a - 2020 leader set a vision for 3 and diverse lead teams the teams and 5 towards management accomplishing hats, employed company my initiatives. experience à Envisioned record savings. for building and implemented synergistic teams. multi-year Optimized roadmaps solutions for three and software teams with towards a proven $1.5 Million track- à Led high the throughput DaaS initiative data pipeline to provide to deliver modernized data at DaaS the by fingertips building of a the partitioned business. Data Lake and à Empowered implementation end-completing to-end 300 legacy business dashboards of data a self-units ecosystem. service with using data the Power Guided ability analytics BI teams upon to portal make a through state-data-that of-driven germinated the-a revamped art decisions DaaS from within analytics via revamping 6 design months. platform and the à Led AWS migration Redshift databases. of data engineering workloads to data stores that are part of on-premises & à Led and data Enterprise combine stewardship. Enterprise Data Governance KPIs evangelizing team under the the principles sponsorship of data of CEO governance, to consolidate, lineage, refine and à Employed and junior a members curated towards career path accelerated to help growth grow senior paths. members into leaders in each team à Reduced portals. remote consulting outlay by 60% via automation and enablement via self-service à Led Implemented project investigations resulted a fraud in reducing to detection design fraud Machine model by 95% to Learning predict and saving algorithms clusters the company of to fraud predict millions activity e-commerce and of dollars. alert. fraud. This à Redesigned reducing timelines and automated by 80%. month end close revenue and margin data for financial systems à Optimized such as Adobe web Analytics, analytics Google in support 360 of and e-Heap commerce Analytics. business operations at scale for tools à Consolidated working with web vendors analytics and internal strategy teams. to aid Product roadmap and Marketing metrics by à Led resource feasibility exploration allocation, of the project. of migration long-term to and cloud short-from term a plans data for perspective the migration developing paths cost and models, overall 3

Experience at Manager Level: 13 years

ZIGNAL (Data 02/2023 Engineering LABS: – 11/2023, 2023 Manager Part of leading Lay-offs an, Advisory 8-member Role engineering Currently) team accomplished - à Real-stack the applications time consisted data pipelines of via Nifi, a stack Kafka, ingesting of microservices. Storm, terabytes S3, Scala, of Databricks, data from social AWS Lambda media sources. functions The serving tech à The such operationalized intelligence The Data platform as Elastic platform from magnitude Search, for the engineered ML unstructured/MongoDB, is Ops almost with applying at RDS Scala semi-a petabyte-50+ and structured and Redis data Apache scale. science for social Spark optimization media models in Databricks posts, in of real-throughput. images to time feed and data to Data derive video. sinks is à Remodeled efficiency engineers for each engineer. to and the deliver effectiveness. team’s quality tech products approaches, Fostered with a sense procedures data quality. of ownership and Developed processes and curated responsibility to empower career pathways amongst towards à Hands-managers. on as necessary leading and stewarding technical brainstorming with tech leads and à Contributed to new product and data science ideas. à Experience APIs. with operationalizing models for Rekognition API, Resnet API and other image ADTERACTIVE: Led effectiveness two teams to to support 2005 excellence - 2007 company with innovation initiatives. in architecture, software practices and operational à Re-production Engineered databases. technical architecture to support data at scale for analytics, reporting, and à Implemented largescale storage SANs to modernize the data platform. SNAPFISH: In and the strengths role 2007 of to a – leader 2016 set a vision for diverse and lead teams the and teams five towards management accomplishing roles, employed company my initiatives. experience à Envisioned record savings. for building and implemented synergistic teams. multi-year Optimized roadmaps solutions for three and software teams with towards a proven $1.5 Million track- à Led high and throughput innovated on by OLTP, implementing Big Data DW hybrid at 300+ cloud Terabyte DBaaS towards scale. four 9’s availability and à Led divestiture. migration of 200+ OLTP DB’s from Oracle to Postgres & MongoDB Atlas as part of HP à Reduced portals. remote consulting outlay by 60% via automation and enablement via self-service à Led resource feasibility exploration allocation, of the project. of migration long-term to and cloud short-from term a plans data for perspective the migration developing paths cost and models, overall à Helped and value. manage IT budget, negotiate contracts with data vendors and optimize for spend 4

Experience at IC Level: 10 Years

MULTIPLE: Production experiences 1995 in DBA important - work 2005 in industries, various namely, deployments supporting Fortune 500 Enterprises and à Financial Services: including Refco & Merrill Lynch. à Telecom Industry: including AT&T.

à Federal Governments Agencies: including FHWA & U.S. Army Corps of Engineers. à Local Governments: including City of Palo Alto.

à e-Commerce: including K-Mart & Homegain.

à

EDUCATION, AWARDS & COURSES

à Master of Science, Engineering, Virginia Tech, Blacksburg, VA à Dwight D. Eisenhower Fellow, U. S. Department of Transportation, Washington D.C. à Advanced level courses in databases, data and analytics related technologies:

§ Oracle Database Administration

§ MongoDB Database Administration

§ Vertica Database Administration

§ PostgreSQL Database Administration

§ Machine Learning

§ Neural Networks

§ Artificial Intelligence

§ Data Insights

à

TECHNICAL SKILLS

à AWS Data MongoDB, GA360, Virtualization. Lake, Cloud, Adobe ScyllaDB, SQL Redshift, Pools, Analytics, Vertica, ML/Spark AI, BI Elastic Pools, Containerization, Viz, Search, Data All Databases Pipelines, Kafka, Hadoop, Databricks, Scala, and Presto, ERP Spark, Pentaho, software, Airflow, PySpark, VMWare, SQL All Postgres, Server, Unix Platform MySQL, flavors, Azure 9,

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