Krishna Mallik Mothiki Email & Phone Number

AWS - Machine Learning Specialty Certified Data Professional with over ten years of data engineering and data science expertise. Experience working in a start-up environment, collaborating with cross-functional units, and leading teams. Highly skilled in building end-to-end Data products and Machine Learning pipelines, for internal stakeholders and customer-facing applications, in finance, marketing, and healthcare domains. The first employee in the Data and Analytics team of currently over 25 members.Building end-to-end data infrastructure: - Data Ingestion to Data Lake (S3 and AWS Cloud Ecosystem) - Batch and Streaming data pipelines (Glue, Lambda, ECS, DMS, AppFlow, Kinesis Firehose) - Data Warehouse and Data Transformation (dbt, Snowflake, Redshift, DynamDB) - Orchestration (Step Functions, Airflow) - Reporting and Reverse ETL (Looker, Hightouch) - Data Governance (dbt, Spectacles, Great expectations) - CI/CD (Docker, Gitlab CI) - Production Deployments for Data Infrastructure (terraform) - Build AI and machine Learning tooling (Snowpark, Streamlit, Langchain, OpenAI & Pinecone)Sources worked on include: a) Salesforce b) NetSuite c) Zendesk d) RingCentral e) Mixpanel f) Workday g) Product data h) Google Sheets i) Google Analytics j) HubSpotExposure to Modern Data Stack and open source ecosystems including Meltano, AirByte, Dagster, and Prefect.A few notable projects: - Built QA bot for Looker dashboards and text to SQL converter using Streamlit, Langchain, and Pinecone. - Designed an end-to-end MLOps repository for the Data Science team using Snowpark ML. - Lead data warehouse migration from Redshift to Snowflake. - Implemented blue/green deployment for dbt repositories. - Parallelized dbt runs and added DynamoDB locking for conflicting data modeling runs. - Added multi-project pipelines in GitLab CI for improved QA and governance. - Created a custom event-based reverse ETL tool. - Automated FP&A reporting. - Migrated batch jobs to near real-time. - Created templates for containerizing and easy deployment of ML models in AWS using Terraform. - Optimized monitoring and alerting."In God we trust, all others must bring data." - W. Edwards Deming

Listed skills include R, Tableau, Microsoft Office, Sql, and 34 others.